<!DOCTYPE html>

<html>

<head>

<meta charset="utf-8" />
<meta name="generator" content="pandoc" />
<meta http-equiv="X-UA-Compatible" content="IE=EDGE" />




<title>corrections_merged</title>

<script>// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
// be compatible with the behavior of Pandoc < 2.8).
document.addEventListener('DOMContentLoaded', function(e) {
  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
  var i, h, a;
  for (i = 0; i < hs.length; i++) {
    h = hs[i];
    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
    a = h.attributes;
    while (a.length > 0) h.removeAttribute(a[0].name);
  }
});
</script>
<script>/*! jQuery v3.6.0 | (c) OpenJS Foundation and other contributors | jquery.org/license */
!function(e,t){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=e.document?t(e,!0):function(e){if(!e.document)throw new Error("jQuery requires a window with a document");return t(e)}:t(e)}("undefined"!=typeof window?window:this,function(C,e){"use strict";var t=[],r=Object.getPrototypeOf,s=t.slice,g=t.flat?function(e){return t.flat.call(e)}:function(e){return t.concat.apply([],e)},u=t.push,i=t.indexOf,n={},o=n.toString,v=n.hasOwnProperty,a=v.toString,l=a.call(Object),y={},m=function(e){return"function"==typeof e&&"number"!=typeof e.nodeType&&"function"!=typeof e.item},x=function(e){return null!=e&&e===e.window},E=C.document,c={type:!0,src:!0,nonce:!0,noModule:!0};function b(e,t,n){var r,i,o=(n=n||E).createElement("script");if(o.text=e,t)for(r in c)(i=t[r]||t.getAttribute&&t.getAttribute(r))&&o.setAttribute(r,i);n.head.appendChild(o).parentNode.removeChild(o)}function w(e){return null==e?e+"":"object"==typeof e||"function"==typeof e?n[o.call(e)]||"object":typeof e}var f="3.6.0",S=function(e,t){return new S.fn.init(e,t)};function p(e){var t=!!e&&"length"in e&&e.length,n=w(e);return!m(e)&&!x(e)&&("array"===n||0===t||"number"==typeof t&&0<t&&t-1 in e)}S.fn=S.prototype={jquery:f,constructor:S,length:0,toArray:function(){return s.call(this)},get:function(e){return null==e?s.call(this):e<0?this[e+this.length]:this[e]},pushStack:function(e){var t=S.merge(this.constructor(),e);return t.prevObject=this,t},each:function(e){return S.each(this,e)},map:function(n){return this.pushStack(S.map(this,function(e,t){return n.call(e,t,e)}))},slice:function(){return this.pushStack(s.apply(this,arguments))},first:function(){return this.eq(0)},last:function(){return this.eq(-1)},even:function(){return this.pushStack(S.grep(this,function(e,t){return(t+1)%2}))},odd:function(){return this.pushStack(S.grep(this,function(e,t){return t%2}))},eq:function(e){var t=this.length,n=+e+(e<0?t:0);return this.pushStack(0<=n&&n<t?[this[n]]:[])},end:function(){return this.prevObject||this.constructor()},push:u,sort:t.sort,splice:t.splice},S.extend=S.fn.extend=function(){var e,t,n,r,i,o,a=arguments[0]||{},s=1,u=arguments.length,l=!1;for("boolean"==typeof a&&(l=a,a=arguments[s]||{},s++),"object"==typeof a||m(a)||(a={}),s===u&&(a=this,s--);s<u;s++)if(null!=(e=arguments[s]))for(t in e)r=e[t],"__proto__"!==t&&a!==r&&(l&&r&&(S.isPlainObject(r)||(i=Array.isArray(r)))?(n=a[t],o=i&&!Array.isArray(n)?[]:i||S.isPlainObject(n)?n:{},i=!1,a[t]=S.extend(l,o,r)):void 0!==r&&(a[t]=r));return a},S.extend({expando:"jQuery"+(f+Math.random()).replace(/\D/g,""),isReady:!0,error:function(e){throw new Error(e)},noop:function(){},isPlainObject:function(e){var t,n;return!(!e||"[object Object]"!==o.call(e))&&(!(t=r(e))||"function"==typeof(n=v.call(t,"constructor")&&t.constructor)&&a.call(n)===l)},isEmptyObject:function(e){var t;for(t in e)return!1;return!0},globalEval:function(e,t,n){b(e,{nonce:t&&t.nonce},n)},each:function(e,t){var n,r=0;if(p(e)){for(n=e.length;r<n;r++)if(!1===t.call(e[r],r,e[r]))break}else for(r in e)if(!1===t.call(e[r],r,e[r]))break;return e},makeArray:function(e,t){var n=t||[];return null!=e&&(p(Object(e))?S.merge(n,"string"==typeof e?[e]:e):u.call(n,e)),n},inArray:function(e,t,n){return null==t?-1:i.call(t,e,n)},merge:function(e,t){for(var n=+t.length,r=0,i=e.length;r<n;r++)e[i++]=t[r];return e.length=i,e},grep:function(e,t,n){for(var r=[],i=0,o=e.length,a=!n;i<o;i++)!t(e[i],i)!==a&&r.push(e[i]);return r},map:function(e,t,n){var r,i,o=0,a=[];if(p(e))for(r=e.length;o<r;o++)null!=(i=t(e[o],o,n))&&a.push(i);else for(o in e)null!=(i=t(e[o],o,n))&&a.push(i);return g(a)},guid:1,support:y}),"function"==typeof Symbol&&(S.fn[Symbol.iterator]=t[Symbol.iterator]),S.each("Boolean Number String Function Array Date RegExp Object Error Symbol".split(" "),function(e,t){n["[object "+t+"]"]=t.toLowerCase()});var d=function(n){var e,d,b,o,i,h,f,g,w,u,l,T,C,a,E,v,s,c,y,S="sizzle"+1*new Date,p=n.document,k=0,r=0,m=ue(),x=ue(),A=ue(),N=ue(),j=function(e,t){return e===t&&(l=!0),0},D={}.hasOwnProperty,t=[],q=t.pop,L=t.push,H=t.push,O=t.slice,P=function(e,t){for(var n=0,r=e.length;n<r;n++)if(e[n]===t)return n;return-1},R="checked|selected|async|autofocus|autoplay|controls|defer|disabled|hidden|ismap|loop|multiple|open|readonly|required|scoped",M="[\\x20\\t\\r\\n\\f]",I="(?:\\\\[\\da-fA-F]{1,6}"+M+"?|\\\\[^\\r\\n\\f]|[\\w-]|[^\0-\\x7f])+",W="\\["+M+"*("+I+")(?:"+M+"*([*^$|!~]?=)"+M+"*(?:'((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\"|("+I+"))|)"+M+"*\\]",F=":("+I+")(?:\\((('((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\")|((?:\\\\.|[^\\\\()[\\]]|"+W+")*)|.*)\\)|)",B=new RegExp(M+"+","g"),$=new RegExp("^"+M+"+|((?:^|[^\\\\])(?:\\\\.)*)"+M+"+$","g"),_=new RegExp("^"+M+"*,"+M+"*"),z=new RegExp("^"+M+"*([>+~]|"+M+")"+M+"*"),U=new RegExp(M+"|>"),X=new RegExp(F),V=new RegExp("^"+I+"$"),G={ID:new RegExp("^#("+I+")"),CLASS:new RegExp("^\\.("+I+")"),TAG:new RegExp("^("+I+"|[*])"),ATTR:new RegExp("^"+W),PSEUDO:new RegExp("^"+F),CHILD:new RegExp("^:(only|first|last|nth|nth-last)-(child|of-type)(?:\\("+M+"*(even|odd|(([+-]|)(\\d*)n|)"+M+"*(?:([+-]|)"+M+"*(\\d+)|))"+M+"*\\)|)","i"),bool:new RegExp("^(?:"+R+")$","i"),needsContext:new RegExp("^"+M+"*[>+~]|:(even|odd|eq|gt|lt|nth|first|last)(?:\\("+M+"*((?:-\\d)?\\d*)"+M+"*\\)|)(?=[^-]|$)","i")},Y=/HTML$/i,Q=/^(?:input|select|textarea|button)$/i,J=/^h\d$/i,K=/^[^{]+\{\s*\[native \w/,Z=/^(?:#([\w-]+)|(\w+)|\.([\w-]+))$/,ee=/[+~]/,te=new RegExp("\\\\[\\da-fA-F]{1,6}"+M+"?|\\\\([^\\r\\n\\f])","g"),ne=function(e,t){var n="0x"+e.slice(1)-65536;return t||(n<0?String.fromCharCode(n+65536):String.fromCharCode(n>>10|55296,1023&n|56320))},re=/([\0-\x1f\x7f]|^-?\d)|^-$|[^\0-\x1f\x7f-\uFFFF\w-]/g,ie=function(e,t){return t?"\0"===e?"\ufffd":e.slice(0,-1)+"\\"+e.charCodeAt(e.length-1).toString(16)+" ":"\\"+e},oe=function(){T()},ae=be(function(e){return!0===e.disabled&&"fieldset"===e.nodeName.toLowerCase()},{dir:"parentNode",next:"legend"});try{H.apply(t=O.call(p.childNodes),p.childNodes),t[p.childNodes.length].nodeType}catch(e){H={apply:t.length?function(e,t){L.apply(e,O.call(t))}:function(e,t){var n=e.length,r=0;while(e[n++]=t[r++]);e.length=n-1}}}function se(t,e,n,r){var i,o,a,s,u,l,c,f=e&&e.ownerDocument,p=e?e.nodeType:9;if(n=n||[],"string"!=typeof t||!t||1!==p&&9!==p&&11!==p)return n;if(!r&&(T(e),e=e||C,E)){if(11!==p&&(u=Z.exec(t)))if(i=u[1]){if(9===p){if(!(a=e.getElementById(i)))return n;if(a.id===i)return n.push(a),n}else if(f&&(a=f.getElementById(i))&&y(e,a)&&a.id===i)return n.push(a),n}else{if(u[2])return H.apply(n,e.getElementsByTagName(t)),n;if((i=u[3])&&d.getElementsByClassName&&e.getElementsByClassName)return H.apply(n,e.getElementsByClassName(i)),n}if(d.qsa&&!N[t+" "]&&(!v||!v.test(t))&&(1!==p||"object"!==e.nodeName.toLowerCase())){if(c=t,f=e,1===p&&(U.test(t)||z.test(t))){(f=ee.test(t)&&ye(e.parentNode)||e)===e&&d.scope||((s=e.getAttribute("id"))?s=s.replace(re,ie):e.setAttribute("id",s=S)),o=(l=h(t)).length;while(o--)l[o]=(s?"#"+s:":scope")+" "+xe(l[o]);c=l.join(",")}try{return H.apply(n,f.querySelectorAll(c)),n}catch(e){N(t,!0)}finally{s===S&&e.removeAttribute("id")}}}return g(t.replace($,"$1"),e,n,r)}function ue(){var r=[];return function e(t,n){return r.push(t+" ")>b.cacheLength&&delete e[r.shift()],e[t+" "]=n}}function le(e){return e[S]=!0,e}function ce(e){var t=C.createElement("fieldset");try{return!!e(t)}catch(e){return!1}finally{t.parentNode&&t.parentNode.removeChild(t),t=null}}function fe(e,t){var n=e.split("|"),r=n.length;while(r--)b.attrHandle[n[r]]=t}function pe(e,t){var n=t&&e,r=n&&1===e.nodeType&&1===t.nodeType&&e.sourceIndex-t.sourceIndex;if(r)return r;if(n)while(n=n.nextSibling)if(n===t)return-1;return e?1:-1}function de(t){return function(e){return"input"===e.nodeName.toLowerCase()&&e.type===t}}function he(n){return function(e){var t=e.nodeName.toLowerCase();return("input"===t||"button"===t)&&e.type===n}}function ge(t){return function(e){return"form"in e?e.parentNode&&!1===e.disabled?"label"in e?"label"in e.parentNode?e.parentNode.disabled===t:e.disabled===t:e.isDisabled===t||e.isDisabled!==!t&&ae(e)===t:e.disabled===t:"label"in e&&e.disabled===t}}function ve(a){return le(function(o){return o=+o,le(function(e,t){var n,r=a([],e.length,o),i=r.length;while(i--)e[n=r[i]]&&(e[n]=!(t[n]=e[n]))})})}function ye(e){return e&&"undefined"!=typeof e.getElementsByTagName&&e}for(e in d=se.support={},i=se.isXML=function(e){var t=e&&e.namespaceURI,n=e&&(e.ownerDocument||e).documentElement;return!Y.test(t||n&&n.nodeName||"HTML")},T=se.setDocument=function(e){var t,n,r=e?e.ownerDocument||e:p;return r!=C&&9===r.nodeType&&r.documentElement&&(a=(C=r).documentElement,E=!i(C),p!=C&&(n=C.defaultView)&&n.top!==n&&(n.addEventListener?n.addEventListener("unload",oe,!1):n.attachEvent&&n.attachEvent("onunload",oe)),d.scope=ce(function(e){return a.appendChild(e).appendChild(C.createElement("div")),"undefined"!=typeof e.querySelectorAll&&!e.querySelectorAll(":scope fieldset div").length}),d.attributes=ce(function(e){return e.className="i",!e.getAttribute("className")}),d.getElementsByTagName=ce(function(e){return e.appendChild(C.createComment("")),!e.getElementsByTagName("*").length}),d.getElementsByClassName=K.test(C.getElementsByClassName),d.getById=ce(function(e){return a.appendChild(e).id=S,!C.getElementsByName||!C.getElementsByName(S).length}),d.getById?(b.filter.ID=function(e){var t=e.replace(te,ne);return function(e){return e.getAttribute("id")===t}},b.find.ID=function(e,t){if("undefined"!=typeof t.getElementById&&E){var n=t.getElementById(e);return n?[n]:[]}}):(b.filter.ID=function(e){var n=e.replace(te,ne);return function(e){var t="undefined"!=typeof e.getAttributeNode&&e.getAttributeNode("id");return t&&t.value===n}},b.find.ID=function(e,t){if("undefined"!=typeof t.getElementById&&E){var n,r,i,o=t.getElementById(e);if(o){if((n=o.getAttributeNode("id"))&&n.value===e)return[o];i=t.getElementsByName(e),r=0;while(o=i[r++])if((n=o.getAttributeNode("id"))&&n.value===e)return[o]}return[]}}),b.find.TAG=d.getElementsByTagName?function(e,t){return"undefined"!=typeof t.getElementsByTagName?t.getElementsByTagName(e):d.qsa?t.querySelectorAll(e):void 0}:function(e,t){var n,r=[],i=0,o=t.getElementsByTagName(e);if("*"===e){while(n=o[i++])1===n.nodeType&&r.push(n);return r}return o},b.find.CLASS=d.getElementsByClassName&&function(e,t){if("undefined"!=typeof t.getElementsByClassName&&E)return t.getElementsByClassName(e)},s=[],v=[],(d.qsa=K.test(C.querySelectorAll))&&(ce(function(e){var t;a.appendChild(e).innerHTML="<a id='"+S+"'></a><select id='"+S+"-\r\\' msallowcapture=''><option selected=''></option></select>",e.querySelectorAll("[msallowcapture^='']").length&&v.push("[*^$]="+M+"*(?:''|\"\")"),e.querySelectorAll("[selected]").length||v.push("\\["+M+"*(?:value|"+R+")"),e.querySelectorAll("[id~="+S+"-]").length||v.push("~="),(t=C.createElement("input")).setAttribute("name",""),e.appendChild(t),e.querySelectorAll("[name='']").length||v.push("\\["+M+"*name"+M+"*="+M+"*(?:''|\"\")"),e.querySelectorAll(":checked").length||v.push(":checked"),e.querySelectorAll("a#"+S+"+*").length||v.push(".#.+[+~]"),e.querySelectorAll("\\\f"),v.push("[\\r\\n\\f]")}),ce(function(e){e.innerHTML="<a href='' disabled='disabled'></a><select disabled='disabled'><option/></select>";var t=C.createElement("input");t.setAttribute("type","hidden"),e.appendChild(t).setAttribute("name","D"),e.querySelectorAll("[name=d]").length&&v.push("name"+M+"*[*^$|!~]?="),2!==e.querySelectorAll(":enabled").length&&v.push(":enabled",":disabled"),a.appendChild(e).disabled=!0,2!==e.querySelectorAll(":disabled").length&&v.push(":enabled",":disabled"),e.querySelectorAll("*,:x"),v.push(",.*:")})),(d.matchesSelector=K.test(c=a.matches||a.webkitMatchesSelector||a.mozMatchesSelector||a.oMatchesSelector||a.msMatchesSelector))&&ce(function(e){d.disconnectedMatch=c.call(e,"*"),c.call(e,"[s!='']:x"),s.push("!=",F)}),v=v.length&&new RegExp(v.join("|")),s=s.length&&new RegExp(s.join("|")),t=K.test(a.compareDocumentPosition),y=t||K.test(a.contains)?function(e,t){var n=9===e.nodeType?e.documentElement:e,r=t&&t.parentNode;return e===r||!(!r||1!==r.nodeType||!(n.contains?n.contains(r):e.compareDocumentPosition&&16&e.compareDocumentPosition(r)))}:function(e,t){if(t)while(t=t.parentNode)if(t===e)return!0;return!1},j=t?function(e,t){if(e===t)return l=!0,0;var n=!e.compareDocumentPosition-!t.compareDocumentPosition;return n||(1&(n=(e.ownerDocument||e)==(t.ownerDocument||t)?e.compareDocumentPosition(t):1)||!d.sortDetached&&t.compareDocumentPosition(e)===n?e==C||e.ownerDocument==p&&y(p,e)?-1:t==C||t.ownerDocument==p&&y(p,t)?1:u?P(u,e)-P(u,t):0:4&n?-1:1)}:function(e,t){if(e===t)return l=!0,0;var n,r=0,i=e.parentNode,o=t.parentNode,a=[e],s=[t];if(!i||!o)return e==C?-1:t==C?1:i?-1:o?1:u?P(u,e)-P(u,t):0;if(i===o)return pe(e,t);n=e;while(n=n.parentNode)a.unshift(n);n=t;while(n=n.parentNode)s.unshift(n);while(a[r]===s[r])r++;return r?pe(a[r],s[r]):a[r]==p?-1:s[r]==p?1:0}),C},se.matches=function(e,t){return se(e,null,null,t)},se.matchesSelector=function(e,t){if(T(e),d.matchesSelector&&E&&!N[t+" "]&&(!s||!s.test(t))&&(!v||!v.test(t)))try{var n=c.call(e,t);if(n||d.disconnectedMatch||e.document&&11!==e.document.nodeType)return n}catch(e){N(t,!0)}return 0<se(t,C,null,[e]).length},se.contains=function(e,t){return(e.ownerDocument||e)!=C&&T(e),y(e,t)},se.attr=function(e,t){(e.ownerDocument||e)!=C&&T(e);var n=b.attrHandle[t.toLowerCase()],r=n&&D.call(b.attrHandle,t.toLowerCase())?n(e,t,!E):void 0;return void 0!==r?r:d.attributes||!E?e.getAttribute(t):(r=e.getAttributeNode(t))&&r.specified?r.value:null},se.escape=function(e){return(e+"").replace(re,ie)},se.error=function(e){throw new Error("Syntax error, unrecognized expression: "+e)},se.uniqueSort=function(e){var t,n=[],r=0,i=0;if(l=!d.detectDuplicates,u=!d.sortStable&&e.slice(0),e.sort(j),l){while(t=e[i++])t===e[i]&&(r=n.push(i));while(r--)e.splice(n[r],1)}return u=null,e},o=se.getText=function(e){var t,n="",r=0,i=e.nodeType;if(i){if(1===i||9===i||11===i){if("string"==typeof e.textContent)return e.textContent;for(e=e.firstChild;e;e=e.nextSibling)n+=o(e)}else if(3===i||4===i)return e.nodeValue}else while(t=e[r++])n+=o(t);return n},(b=se.selectors={cacheLength:50,createPseudo:le,match:G,attrHandle:{},find:{},relative:{">":{dir:"parentNode",first:!0}," ":{dir:"parentNode"},"+":{dir:"previousSibling",first:!0},"~":{dir:"previousSibling"}},preFilter:{ATTR:function(e){return e[1]=e[1].replace(te,ne),e[3]=(e[3]||e[4]||e[5]||"").replace(te,ne),"~="===e[2]&&(e[3]=" "+e[3]+" "),e.slice(0,4)},CHILD:function(e){return e[1]=e[1].toLowerCase(),"nth"===e[1].slice(0,3)?(e[3]||se.error(e[0]),e[4]=+(e[4]?e[5]+(e[6]||1):2*("even"===e[3]||"odd"===e[3])),e[5]=+(e[7]+e[8]||"odd"===e[3])):e[3]&&se.error(e[0]),e},PSEUDO:function(e){var t,n=!e[6]&&e[2];return G.CHILD.test(e[0])?null:(e[3]?e[2]=e[4]||e[5]||"":n&&X.test(n)&&(t=h(n,!0))&&(t=n.indexOf(")",n.length-t)-n.length)&&(e[0]=e[0].slice(0,t),e[2]=n.slice(0,t)),e.slice(0,3))}},filter:{TAG:function(e){var t=e.replace(te,ne).toLowerCase();return"*"===e?function(){return!0}:function(e){return e.nodeName&&e.nodeName.toLowerCase()===t}},CLASS:function(e){var t=m[e+" "];return t||(t=new RegExp("(^|"+M+")"+e+"("+M+"|$)"))&&m(e,function(e){return t.test("string"==typeof e.className&&e.className||"undefined"!=typeof e.getAttribute&&e.getAttribute("class")||"")})},ATTR:function(n,r,i){return function(e){var t=se.attr(e,n);return null==t?"!="===r:!r||(t+="","="===r?t===i:"!="===r?t!==i:"^="===r?i&&0===t.indexOf(i):"*="===r?i&&-1<t.indexOf(i):"$="===r?i&&t.slice(-i.length)===i:"~="===r?-1<(" "+t.replace(B," ")+" ").indexOf(i):"|="===r&&(t===i||t.slice(0,i.length+1)===i+"-"))}},CHILD:function(h,e,t,g,v){var y="nth"!==h.slice(0,3),m="last"!==h.slice(-4),x="of-type"===e;return 1===g&&0===v?function(e){return!!e.parentNode}:function(e,t,n){var r,i,o,a,s,u,l=y!==m?"nextSibling":"previousSibling",c=e.parentNode,f=x&&e.nodeName.toLowerCase(),p=!n&&!x,d=!1;if(c){if(y){while(l){a=e;while(a=a[l])if(x?a.nodeName.toLowerCase()===f:1===a.nodeType)return!1;u=l="only"===h&&!u&&"nextSibling"}return!0}if(u=[m?c.firstChild:c.lastChild],m&&p){d=(s=(r=(i=(o=(a=c)[S]||(a[S]={}))[a.uniqueID]||(o[a.uniqueID]={}))[h]||[])[0]===k&&r[1])&&r[2],a=s&&c.childNodes[s];while(a=++s&&a&&a[l]||(d=s=0)||u.pop())if(1===a.nodeType&&++d&&a===e){i[h]=[k,s,d];break}}else if(p&&(d=s=(r=(i=(o=(a=e)[S]||(a[S]={}))[a.uniqueID]||(o[a.uniqueID]={}))[h]||[])[0]===k&&r[1]),!1===d)while(a=++s&&a&&a[l]||(d=s=0)||u.pop())if((x?a.nodeName.toLowerCase()===f:1===a.nodeType)&&++d&&(p&&((i=(o=a[S]||(a[S]={}))[a.uniqueID]||(o[a.uniqueID]={}))[h]=[k,d]),a===e))break;return(d-=v)===g||d%g==0&&0<=d/g}}},PSEUDO:function(e,o){var t,a=b.pseudos[e]||b.setFilters[e.toLowerCase()]||se.error("unsupported pseudo: "+e);return a[S]?a(o):1<a.length?(t=[e,e,"",o],b.setFilters.hasOwnProperty(e.toLowerCase())?le(function(e,t){var n,r=a(e,o),i=r.length;while(i--)e[n=P(e,r[i])]=!(t[n]=r[i])}):function(e){return a(e,0,t)}):a}},pseudos:{not:le(function(e){var r=[],i=[],s=f(e.replace($,"$1"));return s[S]?le(function(e,t,n,r){var i,o=s(e,null,r,[]),a=e.length;while(a--)(i=o[a])&&(e[a]=!(t[a]=i))}):function(e,t,n){return r[0]=e,s(r,null,n,i),r[0]=null,!i.pop()}}),has:le(function(t){return function(e){return 0<se(t,e).length}}),contains:le(function(t){return t=t.replace(te,ne),function(e){return-1<(e.textContent||o(e)).indexOf(t)}}),lang:le(function(n){return V.test(n||"")||se.error("unsupported lang: "+n),n=n.replace(te,ne).toLowerCase(),function(e){var t;do{if(t=E?e.lang:e.getAttribute("xml:lang")||e.getAttribute("lang"))return(t=t.toLowerCase())===n||0===t.indexOf(n+"-")}while((e=e.parentNode)&&1===e.nodeType);return!1}}),target:function(e){var t=n.location&&n.location.hash;return t&&t.slice(1)===e.id},root:function(e){return e===a},focus:function(e){return e===C.activeElement&&(!C.hasFocus||C.hasFocus())&&!!(e.type||e.href||~e.tabIndex)},enabled:ge(!1),disabled:ge(!0),checked:function(e){var t=e.nodeName.toLowerCase();return"input"===t&&!!e.checked||"option"===t&&!!e.selected},selected:function(e){return e.parentNode&&e.parentNode.selectedIndex,!0===e.selected},empty:function(e){for(e=e.firstChild;e;e=e.nextSibling)if(e.nodeType<6)return!1;return!0},parent:function(e){return!b.pseudos.empty(e)},header:function(e){return J.test(e.nodeName)},input:function(e){return Q.test(e.nodeName)},button:function(e){var t=e.nodeName.toLowerCase();return"input"===t&&"button"===e.type||"button"===t},text:function(e){var t;return"input"===e.nodeName.toLowerCase()&&"text"===e.type&&(null==(t=e.getAttribute("type"))||"text"===t.toLowerCase())},first:ve(function(){return[0]}),last:ve(function(e,t){return[t-1]}),eq:ve(function(e,t,n){return[n<0?n+t:n]}),even:ve(function(e,t){for(var n=0;n<t;n+=2)e.push(n);return e}),odd:ve(function(e,t){for(var n=1;n<t;n+=2)e.push(n);return e}),lt:ve(function(e,t,n){for(var r=n<0?n+t:t<n?t:n;0<=--r;)e.push(r);return e}),gt:ve(function(e,t,n){for(var r=n<0?n+t:n;++r<t;)e.push(r);return e})}}).pseudos.nth=b.pseudos.eq,{radio:!0,checkbox:!0,file:!0,password:!0,image:!0})b.pseudos[e]=de(e);for(e in{submit:!0,reset:!0})b.pseudos[e]=he(e);function me(){}function xe(e){for(var t=0,n=e.length,r="";t<n;t++)r+=e[t].value;return r}function be(s,e,t){var u=e.dir,l=e.next,c=l||u,f=t&&"parentNode"===c,p=r++;return e.first?function(e,t,n){while(e=e[u])if(1===e.nodeType||f)return s(e,t,n);return!1}:function(e,t,n){var r,i,o,a=[k,p];if(n){while(e=e[u])if((1===e.nodeType||f)&&s(e,t,n))return!0}else while(e=e[u])if(1===e.nodeType||f)if(i=(o=e[S]||(e[S]={}))[e.uniqueID]||(o[e.uniqueID]={}),l&&l===e.nodeName.toLowerCase())e=e[u]||e;else{if((r=i[c])&&r[0]===k&&r[1]===p)return a[2]=r[2];if((i[c]=a)[2]=s(e,t,n))return!0}return!1}}function we(i){return 1<i.length?function(e,t,n){var r=i.length;while(r--)if(!i[r](e,t,n))return!1;return!0}:i[0]}function Te(e,t,n,r,i){for(var o,a=[],s=0,u=e.length,l=null!=t;s<u;s++)(o=e[s])&&(n&&!n(o,r,i)||(a.push(o),l&&t.push(s)));return a}function Ce(d,h,g,v,y,e){return v&&!v[S]&&(v=Ce(v)),y&&!y[S]&&(y=Ce(y,e)),le(function(e,t,n,r){var i,o,a,s=[],u=[],l=t.length,c=e||function(e,t,n){for(var r=0,i=t.length;r<i;r++)se(e,t[r],n);return n}(h||"*",n.nodeType?[n]:n,[]),f=!d||!e&&h?c:Te(c,s,d,n,r),p=g?y||(e?d:l||v)?[]:t:f;if(g&&g(f,p,n,r),v){i=Te(p,u),v(i,[],n,r),o=i.length;while(o--)(a=i[o])&&(p[u[o]]=!(f[u[o]]=a))}if(e){if(y||d){if(y){i=[],o=p.length;while(o--)(a=p[o])&&i.push(f[o]=a);y(null,p=[],i,r)}o=p.length;while(o--)(a=p[o])&&-1<(i=y?P(e,a):s[o])&&(e[i]=!(t[i]=a))}}else p=Te(p===t?p.splice(l,p.length):p),y?y(null,t,p,r):H.apply(t,p)})}function Ee(e){for(var i,t,n,r=e.length,o=b.relative[e[0].type],a=o||b.relative[" "],s=o?1:0,u=be(function(e){return e===i},a,!0),l=be(function(e){return-1<P(i,e)},a,!0),c=[function(e,t,n){var r=!o&&(n||t!==w)||((i=t).nodeType?u(e,t,n):l(e,t,n));return i=null,r}];s<r;s++)if(t=b.relative[e[s].type])c=[be(we(c),t)];else{if((t=b.filter[e[s].type].apply(null,e[s].matches))[S]){for(n=++s;n<r;n++)if(b.relative[e[n].type])break;return Ce(1<s&&we(c),1<s&&xe(e.slice(0,s-1).concat({value:" "===e[s-2].type?"*":""})).replace($,"$1"),t,s<n&&Ee(e.slice(s,n)),n<r&&Ee(e=e.slice(n)),n<r&&xe(e))}c.push(t)}return we(c)}return me.prototype=b.filters=b.pseudos,b.setFilters=new me,h=se.tokenize=function(e,t){var n,r,i,o,a,s,u,l=x[e+" "];if(l)return t?0:l.slice(0);a=e,s=[],u=b.preFilter;while(a){for(o in n&&!(r=_.exec(a))||(r&&(a=a.slice(r[0].length)||a),s.push(i=[])),n=!1,(r=z.exec(a))&&(n=r.shift(),i.push({value:n,type:r[0].replace($," ")}),a=a.slice(n.length)),b.filter)!(r=G[o].exec(a))||u[o]&&!(r=u[o](r))||(n=r.shift(),i.push({value:n,type:o,matches:r}),a=a.slice(n.length));if(!n)break}return t?a.length:a?se.error(e):x(e,s).slice(0)},f=se.compile=function(e,t){var n,v,y,m,x,r,i=[],o=[],a=A[e+" "];if(!a){t||(t=h(e)),n=t.length;while(n--)(a=Ee(t[n]))[S]?i.push(a):o.push(a);(a=A(e,(v=o,m=0<(y=i).length,x=0<v.length,r=function(e,t,n,r,i){var o,a,s,u=0,l="0",c=e&&[],f=[],p=w,d=e||x&&b.find.TAG("*",i),h=k+=null==p?1:Math.random()||.1,g=d.length;for(i&&(w=t==C||t||i);l!==g&&null!=(o=d[l]);l++){if(x&&o){a=0,t||o.ownerDocument==C||(T(o),n=!E);while(s=v[a++])if(s(o,t||C,n)){r.push(o);break}i&&(k=h)}m&&((o=!s&&o)&&u--,e&&c.push(o))}if(u+=l,m&&l!==u){a=0;while(s=y[a++])s(c,f,t,n);if(e){if(0<u)while(l--)c[l]||f[l]||(f[l]=q.call(r));f=Te(f)}H.apply(r,f),i&&!e&&0<f.length&&1<u+y.length&&se.uniqueSort(r)}return i&&(k=h,w=p),c},m?le(r):r))).selector=e}return a},g=se.select=function(e,t,n,r){var i,o,a,s,u,l="function"==typeof e&&e,c=!r&&h(e=l.selector||e);if(n=n||[],1===c.length){if(2<(o=c[0]=c[0].slice(0)).length&&"ID"===(a=o[0]).type&&9===t.nodeType&&E&&b.relative[o[1].type]){if(!(t=(b.find.ID(a.matches[0].replace(te,ne),t)||[])[0]))return n;l&&(t=t.parentNode),e=e.slice(o.shift().value.length)}i=G.needsContext.test(e)?0:o.length;while(i--){if(a=o[i],b.relative[s=a.type])break;if((u=b.find[s])&&(r=u(a.matches[0].replace(te,ne),ee.test(o[0].type)&&ye(t.parentNode)||t))){if(o.splice(i,1),!(e=r.length&&xe(o)))return H.apply(n,r),n;break}}}return(l||f(e,c))(r,t,!E,n,!t||ee.test(e)&&ye(t.parentNode)||t),n},d.sortStable=S.split("").sort(j).join("")===S,d.detectDuplicates=!!l,T(),d.sortDetached=ce(function(e){return 1&e.compareDocumentPosition(C.createElement("fieldset"))}),ce(function(e){return e.innerHTML="<a href='#'></a>","#"===e.firstChild.getAttribute("href")})||fe("type|href|height|width",function(e,t,n){if(!n)return e.getAttribute(t,"type"===t.toLowerCase()?1:2)}),d.attributes&&ce(function(e){return e.innerHTML="<input/>",e.firstChild.setAttribute("value",""),""===e.firstChild.getAttribute("value")})||fe("value",function(e,t,n){if(!n&&"input"===e.nodeName.toLowerCase())return e.defaultValue}),ce(function(e){return null==e.getAttribute("disabled")})||fe(R,function(e,t,n){var r;if(!n)return!0===e[t]?t.toLowerCase():(r=e.getAttributeNode(t))&&r.specified?r.value:null}),se}(C);S.find=d,S.expr=d.selectors,S.expr[":"]=S.expr.pseudos,S.uniqueSort=S.unique=d.uniqueSort,S.text=d.getText,S.isXMLDoc=d.isXML,S.contains=d.contains,S.escapeSelector=d.escape;var h=function(e,t,n){var r=[],i=void 0!==n;while((e=e[t])&&9!==e.nodeType)if(1===e.nodeType){if(i&&S(e).is(n))break;r.push(e)}return r},T=function(e,t){for(var n=[];e;e=e.nextSibling)1===e.nodeType&&e!==t&&n.push(e);return n},k=S.expr.match.needsContext;function A(e,t){return e.nodeName&&e.nodeName.toLowerCase()===t.toLowerCase()}var N=/^<([a-z][^\/\0>:\x20\t\r\n\f]*)[\x20\t\r\n\f]*\/?>(?:<\/\1>|)$/i;function j(e,n,r){return m(n)?S.grep(e,function(e,t){return!!n.call(e,t,e)!==r}):n.nodeType?S.grep(e,function(e){return e===n!==r}):"string"!=typeof n?S.grep(e,function(e){return-1<i.call(n,e)!==r}):S.filter(n,e,r)}S.filter=function(e,t,n){var r=t[0];return n&&(e=":not("+e+")"),1===t.length&&1===r.nodeType?S.find.matchesSelector(r,e)?[r]:[]:S.find.matches(e,S.grep(t,function(e){return 1===e.nodeType}))},S.fn.extend({find:function(e){var t,n,r=this.length,i=this;if("string"!=typeof e)return this.pushStack(S(e).filter(function(){for(t=0;t<r;t++)if(S.contains(i[t],this))return!0}));for(n=this.pushStack([]),t=0;t<r;t++)S.find(e,i[t],n);return 1<r?S.uniqueSort(n):n},filter:function(e){return this.pushStack(j(this,e||[],!1))},not:function(e){return this.pushStack(j(this,e||[],!0))},is:function(e){return!!j(this,"string"==typeof e&&k.test(e)?S(e):e||[],!1).length}});var D,q=/^(?:\s*(<[\w\W]+>)[^>]*|#([\w-]+))$/;(S.fn.init=function(e,t,n){var r,i;if(!e)return this;if(n=n||D,"string"==typeof e){if(!(r="<"===e[0]&&">"===e[e.length-1]&&3<=e.length?[null,e,null]:q.exec(e))||!r[1]&&t)return!t||t.jquery?(t||n).find(e):this.constructor(t).find(e);if(r[1]){if(t=t instanceof S?t[0]:t,S.merge(this,S.parseHTML(r[1],t&&t.nodeType?t.ownerDocument||t:E,!0)),N.test(r[1])&&S.isPlainObject(t))for(r in t)m(this[r])?this[r](t[r]):this.attr(r,t[r]);return this}return(i=E.getElementById(r[2]))&&(this[0]=i,this.length=1),this}return e.nodeType?(this[0]=e,this.length=1,this):m(e)?void 0!==n.ready?n.ready(e):e(S):S.makeArray(e,this)}).prototype=S.fn,D=S(E);var L=/^(?:parents|prev(?:Until|All))/,H={children:!0,contents:!0,next:!0,prev:!0};function O(e,t){while((e=e[t])&&1!==e.nodeType);return e}S.fn.extend({has:function(e){var t=S(e,this),n=t.length;return this.filter(function(){for(var e=0;e<n;e++)if(S.contains(this,t[e]))return!0})},closest:function(e,t){var n,r=0,i=this.length,o=[],a="string"!=typeof e&&S(e);if(!k.test(e))for(;r<i;r++)for(n=this[r];n&&n!==t;n=n.parentNode)if(n.nodeType<11&&(a?-1<a.index(n):1===n.nodeType&&S.find.matchesSelector(n,e))){o.push(n);break}return this.pushStack(1<o.length?S.uniqueSort(o):o)},index:function(e){return e?"string"==typeof e?i.call(S(e),this[0]):i.call(this,e.jquery?e[0]:e):this[0]&&this[0].parentNode?this.first().prevAll().length:-1},add:function(e,t){return this.pushStack(S.uniqueSort(S.merge(this.get(),S(e,t))))},addBack:function(e){return this.add(null==e?this.prevObject:this.prevObject.filter(e))}}),S.each({parent:function(e){var t=e.parentNode;return t&&11!==t.nodeType?t:null},parents:function(e){return h(e,"parentNode")},parentsUntil:function(e,t,n){return h(e,"parentNode",n)},next:function(e){return O(e,"nextSibling")},prev:function(e){return O(e,"previousSibling")},nextAll:function(e){return h(e,"nextSibling")},prevAll:function(e){return h(e,"previousSibling")},nextUntil:function(e,t,n){return h(e,"nextSibling",n)},prevUntil:function(e,t,n){return h(e,"previousSibling",n)},siblings:function(e){return T((e.parentNode||{}).firstChild,e)},children:function(e){return T(e.firstChild)},contents:function(e){return null!=e.contentDocument&&r(e.contentDocument)?e.contentDocument:(A(e,"template")&&(e=e.content||e),S.merge([],e.childNodes))}},function(r,i){S.fn[r]=function(e,t){var n=S.map(this,i,e);return"Until"!==r.slice(-5)&&(t=e),t&&"string"==typeof t&&(n=S.filter(t,n)),1<this.length&&(H[r]||S.uniqueSort(n),L.test(r)&&n.reverse()),this.pushStack(n)}});var P=/[^\x20\t\r\n\f]+/g;function R(e){return e}function M(e){throw e}function I(e,t,n,r){var i;try{e&&m(i=e.promise)?i.call(e).done(t).fail(n):e&&m(i=e.then)?i.call(e,t,n):t.apply(void 0,[e].slice(r))}catch(e){n.apply(void 0,[e])}}S.Callbacks=function(r){var e,n;r="string"==typeof r?(e=r,n={},S.each(e.match(P)||[],function(e,t){n[t]=!0}),n):S.extend({},r);var i,t,o,a,s=[],u=[],l=-1,c=function(){for(a=a||r.once,o=i=!0;u.length;l=-1){t=u.shift();while(++l<s.length)!1===s[l].apply(t[0],t[1])&&r.stopOnFalse&&(l=s.length,t=!1)}r.memory||(t=!1),i=!1,a&&(s=t?[]:"")},f={add:function(){return s&&(t&&!i&&(l=s.length-1,u.push(t)),function n(e){S.each(e,function(e,t){m(t)?r.unique&&f.has(t)||s.push(t):t&&t.length&&"string"!==w(t)&&n(t)})}(arguments),t&&!i&&c()),this},remove:function(){return S.each(arguments,function(e,t){var n;while(-1<(n=S.inArray(t,s,n)))s.splice(n,1),n<=l&&l--}),this},has:function(e){return e?-1<S.inArray(e,s):0<s.length},empty:function(){return s&&(s=[]),this},disable:function(){return a=u=[],s=t="",this},disabled:function(){return!s},lock:function(){return a=u=[],t||i||(s=t=""),this},locked:function(){return!!a},fireWith:function(e,t){return a||(t=[e,(t=t||[]).slice?t.slice():t],u.push(t),i||c()),this},fire:function(){return f.fireWith(this,arguments),this},fired:function(){return!!o}};return f},S.extend({Deferred:function(e){var o=[["notify","progress",S.Callbacks("memory"),S.Callbacks("memory"),2],["resolve","done",S.Callbacks("once memory"),S.Callbacks("once memory"),0,"resolved"],["reject","fail",S.Callbacks("once memory"),S.Callbacks("once memory"),1,"rejected"]],i="pending",a={state:function(){return i},always:function(){return s.done(arguments).fail(arguments),this},"catch":function(e){return a.then(null,e)},pipe:function(){var i=arguments;return S.Deferred(function(r){S.each(o,function(e,t){var n=m(i[t[4]])&&i[t[4]];s[t[1]](function(){var e=n&&n.apply(this,arguments);e&&m(e.promise)?e.promise().progress(r.notify).done(r.resolve).fail(r.reject):r[t[0]+"With"](this,n?[e]:arguments)})}),i=null}).promise()},then:function(t,n,r){var u=0;function l(i,o,a,s){return function(){var n=this,r=arguments,e=function(){var e,t;if(!(i<u)){if((e=a.apply(n,r))===o.promise())throw new TypeError("Thenable self-resolution");t=e&&("object"==typeof e||"function"==typeof e)&&e.then,m(t)?s?t.call(e,l(u,o,R,s),l(u,o,M,s)):(u++,t.call(e,l(u,o,R,s),l(u,o,M,s),l(u,o,R,o.notifyWith))):(a!==R&&(n=void 0,r=[e]),(s||o.resolveWith)(n,r))}},t=s?e:function(){try{e()}catch(e){S.Deferred.exceptionHook&&S.Deferred.exceptionHook(e,t.stackTrace),u<=i+1&&(a!==M&&(n=void 0,r=[e]),o.rejectWith(n,r))}};i?t():(S.Deferred.getStackHook&&(t.stackTrace=S.Deferred.getStackHook()),C.setTimeout(t))}}return S.Deferred(function(e){o[0][3].add(l(0,e,m(r)?r:R,e.notifyWith)),o[1][3].add(l(0,e,m(t)?t:R)),o[2][3].add(l(0,e,m(n)?n:M))}).promise()},promise:function(e){return null!=e?S.extend(e,a):a}},s={};return S.each(o,function(e,t){var n=t[2],r=t[5];a[t[1]]=n.add,r&&n.add(function(){i=r},o[3-e][2].disable,o[3-e][3].disable,o[0][2].lock,o[0][3].lock),n.add(t[3].fire),s[t[0]]=function(){return s[t[0]+"With"](this===s?void 0:this,arguments),this},s[t[0]+"With"]=n.fireWith}),a.promise(s),e&&e.call(s,s),s},when:function(e){var n=arguments.length,t=n,r=Array(t),i=s.call(arguments),o=S.Deferred(),a=function(t){return function(e){r[t]=this,i[t]=1<arguments.length?s.call(arguments):e,--n||o.resolveWith(r,i)}};if(n<=1&&(I(e,o.done(a(t)).resolve,o.reject,!n),"pending"===o.state()||m(i[t]&&i[t].then)))return o.then();while(t--)I(i[t],a(t),o.reject);return o.promise()}});var W=/^(Eval|Internal|Range|Reference|Syntax|Type|URI)Error$/;S.Deferred.exceptionHook=function(e,t){C.console&&C.console.warn&&e&&W.test(e.name)&&C.console.warn("jQuery.Deferred exception: "+e.message,e.stack,t)},S.readyException=function(e){C.setTimeout(function(){throw e})};var F=S.Deferred();function B(){E.removeEventListener("DOMContentLoaded",B),C.removeEventListener("load",B),S.ready()}S.fn.ready=function(e){return F.then(e)["catch"](function(e){S.readyException(e)}),this},S.extend({isReady:!1,readyWait:1,ready:function(e){(!0===e?--S.readyWait:S.isReady)||(S.isReady=!0)!==e&&0<--S.readyWait||F.resolveWith(E,[S])}}),S.ready.then=F.then,"complete"===E.readyState||"loading"!==E.readyState&&!E.documentElement.doScroll?C.setTimeout(S.ready):(E.addEventListener("DOMContentLoaded",B),C.addEventListener("load",B));var $=function(e,t,n,r,i,o,a){var s=0,u=e.length,l=null==n;if("object"===w(n))for(s in i=!0,n)$(e,t,s,n[s],!0,o,a);else if(void 0!==r&&(i=!0,m(r)||(a=!0),l&&(a?(t.call(e,r),t=null):(l=t,t=function(e,t,n){return l.call(S(e),n)})),t))for(;s<u;s++)t(e[s],n,a?r:r.call(e[s],s,t(e[s],n)));return i?e:l?t.call(e):u?t(e[0],n):o},_=/^-ms-/,z=/-([a-z])/g;function U(e,t){return t.toUpperCase()}function X(e){return e.replace(_,"ms-").replace(z,U)}var V=function(e){return 1===e.nodeType||9===e.nodeType||!+e.nodeType};function G(){this.expando=S.expando+G.uid++}G.uid=1,G.prototype={cache:function(e){var t=e[this.expando];return t||(t={},V(e)&&(e.nodeType?e[this.expando]=t:Object.defineProperty(e,this.expando,{value:t,configurable:!0}))),t},set:function(e,t,n){var r,i=this.cache(e);if("string"==typeof t)i[X(t)]=n;else for(r in t)i[X(r)]=t[r];return i},get:function(e,t){return void 0===t?this.cache(e):e[this.expando]&&e[this.expando][X(t)]},access:function(e,t,n){return void 0===t||t&&"string"==typeof t&&void 0===n?this.get(e,t):(this.set(e,t,n),void 0!==n?n:t)},remove:function(e,t){var n,r=e[this.expando];if(void 0!==r){if(void 0!==t){n=(t=Array.isArray(t)?t.map(X):(t=X(t))in r?[t]:t.match(P)||[]).length;while(n--)delete r[t[n]]}(void 0===t||S.isEmptyObject(r))&&(e.nodeType?e[this.expando]=void 0:delete e[this.expando])}},hasData:function(e){var t=e[this.expando];return void 0!==t&&!S.isEmptyObject(t)}};var Y=new G,Q=new G,J=/^(?:\{[\w\W]*\}|\[[\w\W]*\])$/,K=/[A-Z]/g;function Z(e,t,n){var r,i;if(void 0===n&&1===e.nodeType)if(r="data-"+t.replace(K,"-$&").toLowerCase(),"string"==typeof(n=e.getAttribute(r))){try{n="true"===(i=n)||"false"!==i&&("null"===i?null:i===+i+""?+i:J.test(i)?JSON.parse(i):i)}catch(e){}Q.set(e,t,n)}else n=void 0;return n}S.extend({hasData:function(e){return Q.hasData(e)||Y.hasData(e)},data:function(e,t,n){return Q.access(e,t,n)},removeData:function(e,t){Q.remove(e,t)},_data:function(e,t,n){return Y.access(e,t,n)},_removeData:function(e,t){Y.remove(e,t)}}),S.fn.extend({data:function(n,e){var t,r,i,o=this[0],a=o&&o.attributes;if(void 0===n){if(this.length&&(i=Q.get(o),1===o.nodeType&&!Y.get(o,"hasDataAttrs"))){t=a.length;while(t--)a[t]&&0===(r=a[t].name).indexOf("data-")&&(r=X(r.slice(5)),Z(o,r,i[r]));Y.set(o,"hasDataAttrs",!0)}return i}return"object"==typeof n?this.each(function(){Q.set(this,n)}):$(this,function(e){var t;if(o&&void 0===e)return void 0!==(t=Q.get(o,n))?t:void 0!==(t=Z(o,n))?t:void 0;this.each(function(){Q.set(this,n,e)})},null,e,1<arguments.length,null,!0)},removeData:function(e){return this.each(function(){Q.remove(this,e)})}}),S.extend({queue:function(e,t,n){var r;if(e)return t=(t||"fx")+"queue",r=Y.get(e,t),n&&(!r||Array.isArray(n)?r=Y.access(e,t,S.makeArray(n)):r.push(n)),r||[]},dequeue:function(e,t){t=t||"fx";var n=S.queue(e,t),r=n.length,i=n.shift(),o=S._queueHooks(e,t);"inprogress"===i&&(i=n.shift(),r--),i&&("fx"===t&&n.unshift("inprogress"),delete o.stop,i.call(e,function(){S.dequeue(e,t)},o)),!r&&o&&o.empty.fire()},_queueHooks:function(e,t){var n=t+"queueHooks";return Y.get(e,n)||Y.access(e,n,{empty:S.Callbacks("once memory").add(function(){Y.remove(e,[t+"queue",n])})})}}),S.fn.extend({queue:function(t,n){var e=2;return"string"!=typeof t&&(n=t,t="fx",e--),arguments.length<e?S.queue(this[0],t):void 0===n?this:this.each(function(){var e=S.queue(this,t,n);S._queueHooks(this,t),"fx"===t&&"inprogress"!==e[0]&&S.dequeue(this,t)})},dequeue:function(e){return this.each(function(){S.dequeue(this,e)})},clearQueue:function(e){return this.queue(e||"fx",[])},promise:function(e,t){var n,r=1,i=S.Deferred(),o=this,a=this.length,s=function(){--r||i.resolveWith(o,[o])};"string"!=typeof e&&(t=e,e=void 0),e=e||"fx";while(a--)(n=Y.get(o[a],e+"queueHooks"))&&n.empty&&(r++,n.empty.add(s));return s(),i.promise(t)}});var ee=/[+-]?(?:\d*\.|)\d+(?:[eE][+-]?\d+|)/.source,te=new RegExp("^(?:([+-])=|)("+ee+")([a-z%]*)$","i"),ne=["Top","Right","Bottom","Left"],re=E.documentElement,ie=function(e){return S.contains(e.ownerDocument,e)},oe={composed:!0};re.getRootNode&&(ie=function(e){return S.contains(e.ownerDocument,e)||e.getRootNode(oe)===e.ownerDocument});var ae=function(e,t){return"none"===(e=t||e).style.display||""===e.style.display&&ie(e)&&"none"===S.css(e,"display")};function se(e,t,n,r){var i,o,a=20,s=r?function(){return r.cur()}:function(){return S.css(e,t,"")},u=s(),l=n&&n[3]||(S.cssNumber[t]?"":"px"),c=e.nodeType&&(S.cssNumber[t]||"px"!==l&&+u)&&te.exec(S.css(e,t));if(c&&c[3]!==l){u/=2,l=l||c[3],c=+u||1;while(a--)S.style(e,t,c+l),(1-o)*(1-(o=s()/u||.5))<=0&&(a=0),c/=o;c*=2,S.style(e,t,c+l),n=n||[]}return n&&(c=+c||+u||0,i=n[1]?c+(n[1]+1)*n[2]:+n[2],r&&(r.unit=l,r.start=c,r.end=i)),i}var ue={};function le(e,t){for(var n,r,i,o,a,s,u,l=[],c=0,f=e.length;c<f;c++)(r=e[c]).style&&(n=r.style.display,t?("none"===n&&(l[c]=Y.get(r,"display")||null,l[c]||(r.style.display="")),""===r.style.display&&ae(r)&&(l[c]=(u=a=o=void 0,a=(i=r).ownerDocument,s=i.nodeName,(u=ue[s])||(o=a.body.appendChild(a.createElement(s)),u=S.css(o,"display"),o.parentNode.removeChild(o),"none"===u&&(u="block"),ue[s]=u)))):"none"!==n&&(l[c]="none",Y.set(r,"display",n)));for(c=0;c<f;c++)null!=l[c]&&(e[c].style.display=l[c]);return e}S.fn.extend({show:function(){return le(this,!0)},hide:function(){return le(this)},toggle:function(e){return"boolean"==typeof e?e?this.show():this.hide():this.each(function(){ae(this)?S(this).show():S(this).hide()})}});var ce,fe,pe=/^(?:checkbox|radio)$/i,de=/<([a-z][^\/\0>\x20\t\r\n\f]*)/i,he=/^$|^module$|\/(?:java|ecma)script/i;ce=E.createDocumentFragment().appendChild(E.createElement("div")),(fe=E.createElement("input")).setAttribute("type","radio"),fe.setAttribute("checked","checked"),fe.setAttribute("name","t"),ce.appendChild(fe),y.checkClone=ce.cloneNode(!0).cloneNode(!0).lastChild.checked,ce.innerHTML="<textarea>x</textarea>",y.noCloneChecked=!!ce.cloneNode(!0).lastChild.defaultValue,ce.innerHTML="<option></option>",y.option=!!ce.lastChild;var ge={thead:[1,"<table>","</table>"],col:[2,"<table><colgroup>","</colgroup></table>"],tr:[2,"<table><tbody>","</tbody></table>"],td:[3,"<table><tbody><tr>","</tr></tbody></table>"],_default:[0,"",""]};function ve(e,t){var n;return n="undefined"!=typeof e.getElementsByTagName?e.getElementsByTagName(t||"*"):"undefined"!=typeof e.querySelectorAll?e.querySelectorAll(t||"*"):[],void 0===t||t&&A(e,t)?S.merge([e],n):n}function ye(e,t){for(var n=0,r=e.length;n<r;n++)Y.set(e[n],"globalEval",!t||Y.get(t[n],"globalEval"))}ge.tbody=ge.tfoot=ge.colgroup=ge.caption=ge.thead,ge.th=ge.td,y.option||(ge.optgroup=ge.option=[1,"<select multiple='multiple'>","</select>"]);var me=/<|&#?\w+;/;function xe(e,t,n,r,i){for(var o,a,s,u,l,c,f=t.createDocumentFragment(),p=[],d=0,h=e.length;d<h;d++)if((o=e[d])||0===o)if("object"===w(o))S.merge(p,o.nodeType?[o]:o);else if(me.test(o)){a=a||f.appendChild(t.createElement("div")),s=(de.exec(o)||["",""])[1].toLowerCase(),u=ge[s]||ge._default,a.innerHTML=u[1]+S.htmlPrefilter(o)+u[2],c=u[0];while(c--)a=a.lastChild;S.merge(p,a.childNodes),(a=f.firstChild).textContent=""}else p.push(t.createTextNode(o));f.textContent="",d=0;while(o=p[d++])if(r&&-1<S.inArray(o,r))i&&i.push(o);else if(l=ie(o),a=ve(f.appendChild(o),"script"),l&&ye(a),n){c=0;while(o=a[c++])he.test(o.type||"")&&n.push(o)}return f}var be=/^([^.]*)(?:\.(.+)|)/;function we(){return!0}function Te(){return!1}function Ce(e,t){return e===function(){try{return E.activeElement}catch(e){}}()==("focus"===t)}function Ee(e,t,n,r,i,o){var a,s;if("object"==typeof t){for(s in"string"!=typeof n&&(r=r||n,n=void 0),t)Ee(e,s,n,r,t[s],o);return e}if(null==r&&null==i?(i=n,r=n=void 0):null==i&&("string"==typeof n?(i=r,r=void 0):(i=r,r=n,n=void 0)),!1===i)i=Te;else if(!i)return e;return 1===o&&(a=i,(i=function(e){return S().off(e),a.apply(this,arguments)}).guid=a.guid||(a.guid=S.guid++)),e.each(function(){S.event.add(this,t,i,r,n)})}function Se(e,i,o){o?(Y.set(e,i,!1),S.event.add(e,i,{namespace:!1,handler:function(e){var t,n,r=Y.get(this,i);if(1&e.isTrigger&&this[i]){if(r.length)(S.event.special[i]||{}).delegateType&&e.stopPropagation();else if(r=s.call(arguments),Y.set(this,i,r),t=o(this,i),this[i](),r!==(n=Y.get(this,i))||t?Y.set(this,i,!1):n={},r!==n)return e.stopImmediatePropagation(),e.preventDefault(),n&&n.value}else r.length&&(Y.set(this,i,{value:S.event.trigger(S.extend(r[0],S.Event.prototype),r.slice(1),this)}),e.stopImmediatePropagation())}})):void 0===Y.get(e,i)&&S.event.add(e,i,we)}S.event={global:{},add:function(t,e,n,r,i){var o,a,s,u,l,c,f,p,d,h,g,v=Y.get(t);if(V(t)){n.handler&&(n=(o=n).handler,i=o.selector),i&&S.find.matchesSelector(re,i),n.guid||(n.guid=S.guid++),(u=v.events)||(u=v.events=Object.create(null)),(a=v.handle)||(a=v.handle=function(e){return"undefined"!=typeof S&&S.event.triggered!==e.type?S.event.dispatch.apply(t,arguments):void 0}),l=(e=(e||"").match(P)||[""]).length;while(l--)d=g=(s=be.exec(e[l])||[])[1],h=(s[2]||"").split(".").sort(),d&&(f=S.event.special[d]||{},d=(i?f.delegateType:f.bindType)||d,f=S.event.special[d]||{},c=S.extend({type:d,origType:g,data:r,handler:n,guid:n.guid,selector:i,needsContext:i&&S.expr.match.needsContext.test(i),namespace:h.join(".")},o),(p=u[d])||((p=u[d]=[]).delegateCount=0,f.setup&&!1!==f.setup.call(t,r,h,a)||t.addEventListener&&t.addEventListener(d,a)),f.add&&(f.add.call(t,c),c.handler.guid||(c.handler.guid=n.guid)),i?p.splice(p.delegateCount++,0,c):p.push(c),S.event.global[d]=!0)}},remove:function(e,t,n,r,i){var o,a,s,u,l,c,f,p,d,h,g,v=Y.hasData(e)&&Y.get(e);if(v&&(u=v.events)){l=(t=(t||"").match(P)||[""]).length;while(l--)if(d=g=(s=be.exec(t[l])||[])[1],h=(s[2]||"").split(".").sort(),d){f=S.event.special[d]||{},p=u[d=(r?f.delegateType:f.bindType)||d]||[],s=s[2]&&new RegExp("(^|\\.)"+h.join("\\.(?:.*\\.|)")+"(\\.|$)"),a=o=p.length;while(o--)c=p[o],!i&&g!==c.origType||n&&n.guid!==c.guid||s&&!s.test(c.namespace)||r&&r!==c.selector&&("**"!==r||!c.selector)||(p.splice(o,1),c.selector&&p.delegateCount--,f.remove&&f.remove.call(e,c));a&&!p.length&&(f.teardown&&!1!==f.teardown.call(e,h,v.handle)||S.removeEvent(e,d,v.handle),delete u[d])}else for(d in u)S.event.remove(e,d+t[l],n,r,!0);S.isEmptyObject(u)&&Y.remove(e,"handle events")}},dispatch:function(e){var t,n,r,i,o,a,s=new Array(arguments.length),u=S.event.fix(e),l=(Y.get(this,"events")||Object.create(null))[u.type]||[],c=S.event.special[u.type]||{};for(s[0]=u,t=1;t<arguments.length;t++)s[t]=arguments[t];if(u.delegateTarget=this,!c.preDispatch||!1!==c.preDispatch.call(this,u)){a=S.event.handlers.call(this,u,l),t=0;while((i=a[t++])&&!u.isPropagationStopped()){u.currentTarget=i.elem,n=0;while((o=i.handlers[n++])&&!u.isImmediatePropagationStopped())u.rnamespace&&!1!==o.namespace&&!u.rnamespace.test(o.namespace)||(u.handleObj=o,u.data=o.data,void 0!==(r=((S.event.special[o.origType]||{}).handle||o.handler).apply(i.elem,s))&&!1===(u.result=r)&&(u.preventDefault(),u.stopPropagation()))}return c.postDispatch&&c.postDispatch.call(this,u),u.result}},handlers:function(e,t){var n,r,i,o,a,s=[],u=t.delegateCount,l=e.target;if(u&&l.nodeType&&!("click"===e.type&&1<=e.button))for(;l!==this;l=l.parentNode||this)if(1===l.nodeType&&("click"!==e.type||!0!==l.disabled)){for(o=[],a={},n=0;n<u;n++)void 0===a[i=(r=t[n]).selector+" "]&&(a[i]=r.needsContext?-1<S(i,this).index(l):S.find(i,this,null,[l]).length),a[i]&&o.push(r);o.length&&s.push({elem:l,handlers:o})}return l=this,u<t.length&&s.push({elem:l,handlers:t.slice(u)}),s},addProp:function(t,e){Object.defineProperty(S.Event.prototype,t,{enumerable:!0,configurable:!0,get:m(e)?function(){if(this.originalEvent)return e(this.originalEvent)}:function(){if(this.originalEvent)return this.originalEvent[t]},set:function(e){Object.defineProperty(this,t,{enumerable:!0,configurable:!0,writable:!0,value:e})}})},fix:function(e){return e[S.expando]?e:new S.Event(e)},special:{load:{noBubble:!0},click:{setup:function(e){var t=this||e;return pe.test(t.type)&&t.click&&A(t,"input")&&Se(t,"click",we),!1},trigger:function(e){var t=this||e;return pe.test(t.type)&&t.click&&A(t,"input")&&Se(t,"click"),!0},_default:function(e){var t=e.target;return pe.test(t.type)&&t.click&&A(t,"input")&&Y.get(t,"click")||A(t,"a")}},beforeunload:{postDispatch:function(e){void 0!==e.result&&e.originalEvent&&(e.originalEvent.returnValue=e.result)}}}},S.removeEvent=function(e,t,n){e.removeEventListener&&e.removeEventListener(t,n)},S.Event=function(e,t){if(!(this instanceof S.Event))return new S.Event(e,t);e&&e.type?(this.originalEvent=e,this.type=e.type,this.isDefaultPrevented=e.defaultPrevented||void 0===e.defaultPrevented&&!1===e.returnValue?we:Te,this.target=e.target&&3===e.target.nodeType?e.target.parentNode:e.target,this.currentTarget=e.currentTarget,this.relatedTarget=e.relatedTarget):this.type=e,t&&S.extend(this,t),this.timeStamp=e&&e.timeStamp||Date.now(),this[S.expando]=!0},S.Event.prototype={constructor:S.Event,isDefaultPrevented:Te,isPropagationStopped:Te,isImmediatePropagationStopped:Te,isSimulated:!1,preventDefault:function(){var e=this.originalEvent;this.isDefaultPrevented=we,e&&!this.isSimulated&&e.preventDefault()},stopPropagation:function(){var e=this.originalEvent;this.isPropagationStopped=we,e&&!this.isSimulated&&e.stopPropagation()},stopImmediatePropagation:function(){var e=this.originalEvent;this.isImmediatePropagationStopped=we,e&&!this.isSimulated&&e.stopImmediatePropagation(),this.stopPropagation()}},S.each({altKey:!0,bubbles:!0,cancelable:!0,changedTouches:!0,ctrlKey:!0,detail:!0,eventPhase:!0,metaKey:!0,pageX:!0,pageY:!0,shiftKey:!0,view:!0,"char":!0,code:!0,charCode:!0,key:!0,keyCode:!0,button:!0,buttons:!0,clientX:!0,clientY:!0,offsetX:!0,offsetY:!0,pointerId:!0,pointerType:!0,screenX:!0,screenY:!0,targetTouches:!0,toElement:!0,touches:!0,which:!0},S.event.addProp),S.each({focus:"focusin",blur:"focusout"},function(e,t){S.event.special[e]={setup:function(){return Se(this,e,Ce),!1},trigger:function(){return Se(this,e),!0},_default:function(){return!0},delegateType:t}}),S.each({mouseenter:"mouseover",mouseleave:"mouseout",pointerenter:"pointerover",pointerleave:"pointerout"},function(e,i){S.event.special[e]={delegateType:i,bindType:i,handle:function(e){var t,n=e.relatedTarget,r=e.handleObj;return n&&(n===this||S.contains(this,n))||(e.type=r.origType,t=r.handler.apply(this,arguments),e.type=i),t}}}),S.fn.extend({on:function(e,t,n,r){return Ee(this,e,t,n,r)},one:function(e,t,n,r){return Ee(this,e,t,n,r,1)},off:function(e,t,n){var r,i;if(e&&e.preventDefault&&e.handleObj)return r=e.handleObj,S(e.delegateTarget).off(r.namespace?r.origType+"."+r.namespace:r.origType,r.selector,r.handler),this;if("object"==typeof e){for(i in e)this.off(i,t,e[i]);return this}return!1!==t&&"function"!=typeof t||(n=t,t=void 0),!1===n&&(n=Te),this.each(function(){S.event.remove(this,e,n,t)})}});var ke=/<script|<style|<link/i,Ae=/checked\s*(?:[^=]|=\s*.checked.)/i,Ne=/^\s*<!(?:\[CDATA\[|--)|(?:\]\]|--)>\s*$/g;function je(e,t){return A(e,"table")&&A(11!==t.nodeType?t:t.firstChild,"tr")&&S(e).children("tbody")[0]||e}function De(e){return e.type=(null!==e.getAttribute("type"))+"/"+e.type,e}function qe(e){return"true/"===(e.type||"").slice(0,5)?e.type=e.type.slice(5):e.removeAttribute("type"),e}function Le(e,t){var n,r,i,o,a,s;if(1===t.nodeType){if(Y.hasData(e)&&(s=Y.get(e).events))for(i in Y.remove(t,"handle events"),s)for(n=0,r=s[i].length;n<r;n++)S.event.add(t,i,s[i][n]);Q.hasData(e)&&(o=Q.access(e),a=S.extend({},o),Q.set(t,a))}}function He(n,r,i,o){r=g(r);var e,t,a,s,u,l,c=0,f=n.length,p=f-1,d=r[0],h=m(d);if(h||1<f&&"string"==typeof d&&!y.checkClone&&Ae.test(d))return n.each(function(e){var t=n.eq(e);h&&(r[0]=d.call(this,e,t.html())),He(t,r,i,o)});if(f&&(t=(e=xe(r,n[0].ownerDocument,!1,n,o)).firstChild,1===e.childNodes.length&&(e=t),t||o)){for(s=(a=S.map(ve(e,"script"),De)).length;c<f;c++)u=e,c!==p&&(u=S.clone(u,!0,!0),s&&S.merge(a,ve(u,"script"))),i.call(n[c],u,c);if(s)for(l=a[a.length-1].ownerDocument,S.map(a,qe),c=0;c<s;c++)u=a[c],he.test(u.type||"")&&!Y.access(u,"globalEval")&&S.contains(l,u)&&(u.src&&"module"!==(u.type||"").toLowerCase()?S._evalUrl&&!u.noModule&&S._evalUrl(u.src,{nonce:u.nonce||u.getAttribute("nonce")},l):b(u.textContent.replace(Ne,""),u,l))}return n}function Oe(e,t,n){for(var r,i=t?S.filter(t,e):e,o=0;null!=(r=i[o]);o++)n||1!==r.nodeType||S.cleanData(ve(r)),r.parentNode&&(n&&ie(r)&&ye(ve(r,"script")),r.parentNode.removeChild(r));return e}S.extend({htmlPrefilter:function(e){return e},clone:function(e,t,n){var r,i,o,a,s,u,l,c=e.cloneNode(!0),f=ie(e);if(!(y.noCloneChecked||1!==e.nodeType&&11!==e.nodeType||S.isXMLDoc(e)))for(a=ve(c),r=0,i=(o=ve(e)).length;r<i;r++)s=o[r],u=a[r],void 0,"input"===(l=u.nodeName.toLowerCase())&&pe.test(s.type)?u.checked=s.checked:"input"!==l&&"textarea"!==l||(u.defaultValue=s.defaultValue);if(t)if(n)for(o=o||ve(e),a=a||ve(c),r=0,i=o.length;r<i;r++)Le(o[r],a[r]);else Le(e,c);return 0<(a=ve(c,"script")).length&&ye(a,!f&&ve(e,"script")),c},cleanData:function(e){for(var t,n,r,i=S.event.special,o=0;void 0!==(n=e[o]);o++)if(V(n)){if(t=n[Y.expando]){if(t.events)for(r in t.events)i[r]?S.event.remove(n,r):S.removeEvent(n,r,t.handle);n[Y.expando]=void 0}n[Q.expando]&&(n[Q.expando]=void 0)}}}),S.fn.extend({detach:function(e){return Oe(this,e,!0)},remove:function(e){return Oe(this,e)},text:function(e){return $(this,function(e){return void 0===e?S.text(this):this.empty().each(function(){1!==this.nodeType&&11!==this.nodeType&&9!==this.nodeType||(this.textContent=e)})},null,e,arguments.length)},append:function(){return He(this,arguments,function(e){1!==this.nodeType&&11!==this.nodeType&&9!==this.nodeType||je(this,e).appendChild(e)})},prepend:function(){return He(this,arguments,function(e){if(1===this.nodeType||11===this.nodeType||9===this.nodeType){var t=je(this,e);t.insertBefore(e,t.firstChild)}})},before:function(){return He(this,arguments,function(e){this.parentNode&&this.parentNode.insertBefore(e,this)})},after:function(){return He(this,arguments,function(e){this.parentNode&&this.parentNode.insertBefore(e,this.nextSibling)})},empty:function(){for(var e,t=0;null!=(e=this[t]);t++)1===e.nodeType&&(S.cleanData(ve(e,!1)),e.textContent="");return this},clone:function(e,t){return e=null!=e&&e,t=null==t?e:t,this.map(function(){return S.clone(this,e,t)})},html:function(e){return $(this,function(e){var t=this[0]||{},n=0,r=this.length;if(void 0===e&&1===t.nodeType)return t.innerHTML;if("string"==typeof e&&!ke.test(e)&&!ge[(de.exec(e)||["",""])[1].toLowerCase()]){e=S.htmlPrefilter(e);try{for(;n<r;n++)1===(t=this[n]||{}).nodeType&&(S.cleanData(ve(t,!1)),t.innerHTML=e);t=0}catch(e){}}t&&this.empty().append(e)},null,e,arguments.length)},replaceWith:function(){var n=[];return He(this,arguments,function(e){var t=this.parentNode;S.inArray(this,n)<0&&(S.cleanData(ve(this)),t&&t.replaceChild(e,this))},n)}}),S.each({appendTo:"append",prependTo:"prepend",insertBefore:"before",insertAfter:"after",replaceAll:"replaceWith"},function(e,a){S.fn[e]=function(e){for(var t,n=[],r=S(e),i=r.length-1,o=0;o<=i;o++)t=o===i?this:this.clone(!0),S(r[o])[a](t),u.apply(n,t.get());return this.pushStack(n)}});var Pe=new RegExp("^("+ee+")(?!px)[a-z%]+$","i"),Re=function(e){var t=e.ownerDocument.defaultView;return t&&t.opener||(t=C),t.getComputedStyle(e)},Me=function(e,t,n){var r,i,o={};for(i in t)o[i]=e.style[i],e.style[i]=t[i];for(i in r=n.call(e),t)e.style[i]=o[i];return r},Ie=new RegExp(ne.join("|"),"i");function We(e,t,n){var r,i,o,a,s=e.style;return(n=n||Re(e))&&(""!==(a=n.getPropertyValue(t)||n[t])||ie(e)||(a=S.style(e,t)),!y.pixelBoxStyles()&&Pe.test(a)&&Ie.test(t)&&(r=s.width,i=s.minWidth,o=s.maxWidth,s.minWidth=s.maxWidth=s.width=a,a=n.width,s.width=r,s.minWidth=i,s.maxWidth=o)),void 0!==a?a+"":a}function Fe(e,t){return{get:function(){if(!e())return(this.get=t).apply(this,arguments);delete this.get}}}!function(){function e(){if(l){u.style.cssText="position:absolute;left:-11111px;width:60px;margin-top:1px;padding:0;border:0",l.style.cssText="position:relative;display:block;box-sizing:border-box;overflow:scroll;margin:auto;border:1px;padding:1px;width:60%;top:1%",re.appendChild(u).appendChild(l);var e=C.getComputedStyle(l);n="1%"!==e.top,s=12===t(e.marginLeft),l.style.right="60%",o=36===t(e.right),r=36===t(e.width),l.style.position="absolute",i=12===t(l.offsetWidth/3),re.removeChild(u),l=null}}function t(e){return Math.round(parseFloat(e))}var n,r,i,o,a,s,u=E.createElement("div"),l=E.createElement("div");l.style&&(l.style.backgroundClip="content-box",l.cloneNode(!0).style.backgroundClip="",y.clearCloneStyle="content-box"===l.style.backgroundClip,S.extend(y,{boxSizingReliable:function(){return e(),r},pixelBoxStyles:function(){return e(),o},pixelPosition:function(){return e(),n},reliableMarginLeft:function(){return e(),s},scrollboxSize:function(){return e(),i},reliableTrDimensions:function(){var e,t,n,r;return null==a&&(e=E.createElement("table"),t=E.createElement("tr"),n=E.createElement("div"),e.style.cssText="position:absolute;left:-11111px;border-collapse:separate",t.style.cssText="border:1px solid",t.style.height="1px",n.style.height="9px",n.style.display="block",re.appendChild(e).appendChild(t).appendChild(n),r=C.getComputedStyle(t),a=parseInt(r.height,10)+parseInt(r.borderTopWidth,10)+parseInt(r.borderBottomWidth,10)===t.offsetHeight,re.removeChild(e)),a}}))}();var Be=["Webkit","Moz","ms"],$e=E.createElement("div").style,_e={};function ze(e){var t=S.cssProps[e]||_e[e];return t||(e in $e?e:_e[e]=function(e){var t=e[0].toUpperCase()+e.slice(1),n=Be.length;while(n--)if((e=Be[n]+t)in $e)return e}(e)||e)}var Ue=/^(none|table(?!-c[ea]).+)/,Xe=/^--/,Ve={position:"absolute",visibility:"hidden",display:"block"},Ge={letterSpacing:"0",fontWeight:"400"};function Ye(e,t,n){var r=te.exec(t);return r?Math.max(0,r[2]-(n||0))+(r[3]||"px"):t}function Qe(e,t,n,r,i,o){var a="width"===t?1:0,s=0,u=0;if(n===(r?"border":"content"))return 0;for(;a<4;a+=2)"margin"===n&&(u+=S.css(e,n+ne[a],!0,i)),r?("content"===n&&(u-=S.css(e,"padding"+ne[a],!0,i)),"margin"!==n&&(u-=S.css(e,"border"+ne[a]+"Width",!0,i))):(u+=S.css(e,"padding"+ne[a],!0,i),"padding"!==n?u+=S.css(e,"border"+ne[a]+"Width",!0,i):s+=S.css(e,"border"+ne[a]+"Width",!0,i));return!r&&0<=o&&(u+=Math.max(0,Math.ceil(e["offset"+t[0].toUpperCase()+t.slice(1)]-o-u-s-.5))||0),u}function Je(e,t,n){var r=Re(e),i=(!y.boxSizingReliable()||n)&&"border-box"===S.css(e,"boxSizing",!1,r),o=i,a=We(e,t,r),s="offset"+t[0].toUpperCase()+t.slice(1);if(Pe.test(a)){if(!n)return a;a="auto"}return(!y.boxSizingReliable()&&i||!y.reliableTrDimensions()&&A(e,"tr")||"auto"===a||!parseFloat(a)&&"inline"===S.css(e,"display",!1,r))&&e.getClientRects().length&&(i="border-box"===S.css(e,"boxSizing",!1,r),(o=s in e)&&(a=e[s])),(a=parseFloat(a)||0)+Qe(e,t,n||(i?"border":"content"),o,r,a)+"px"}function Ke(e,t,n,r,i){return new Ke.prototype.init(e,t,n,r,i)}S.extend({cssHooks:{opacity:{get:function(e,t){if(t){var n=We(e,"opacity");return""===n?"1":n}}}},cssNumber:{animationIterationCount:!0,columnCount:!0,fillOpacity:!0,flexGrow:!0,flexShrink:!0,fontWeight:!0,gridArea:!0,gridColumn:!0,gridColumnEnd:!0,gridColumnStart:!0,gridRow:!0,gridRowEnd:!0,gridRowStart:!0,lineHeight:!0,opacity:!0,order:!0,orphans:!0,widows:!0,zIndex:!0,zoom:!0},cssProps:{},style:function(e,t,n,r){if(e&&3!==e.nodeType&&8!==e.nodeType&&e.style){var i,o,a,s=X(t),u=Xe.test(t),l=e.style;if(u||(t=ze(s)),a=S.cssHooks[t]||S.cssHooks[s],void 0===n)return a&&"get"in a&&void 0!==(i=a.get(e,!1,r))?i:l[t];"string"===(o=typeof n)&&(i=te.exec(n))&&i[1]&&(n=se(e,t,i),o="number"),null!=n&&n==n&&("number"!==o||u||(n+=i&&i[3]||(S.cssNumber[s]?"":"px")),y.clearCloneStyle||""!==n||0!==t.indexOf("background")||(l[t]="inherit"),a&&"set"in a&&void 0===(n=a.set(e,n,r))||(u?l.setProperty(t,n):l[t]=n))}},css:function(e,t,n,r){var i,o,a,s=X(t);return Xe.test(t)||(t=ze(s)),(a=S.cssHooks[t]||S.cssHooks[s])&&"get"in a&&(i=a.get(e,!0,n)),void 0===i&&(i=We(e,t,r)),"normal"===i&&t in Ge&&(i=Ge[t]),""===n||n?(o=parseFloat(i),!0===n||isFinite(o)?o||0:i):i}}),S.each(["height","width"],function(e,u){S.cssHooks[u]={get:function(e,t,n){if(t)return!Ue.test(S.css(e,"display"))||e.getClientRects().length&&e.getBoundingClientRect().width?Je(e,u,n):Me(e,Ve,function(){return Je(e,u,n)})},set:function(e,t,n){var r,i=Re(e),o=!y.scrollboxSize()&&"absolute"===i.position,a=(o||n)&&"border-box"===S.css(e,"boxSizing",!1,i),s=n?Qe(e,u,n,a,i):0;return a&&o&&(s-=Math.ceil(e["offset"+u[0].toUpperCase()+u.slice(1)]-parseFloat(i[u])-Qe(e,u,"border",!1,i)-.5)),s&&(r=te.exec(t))&&"px"!==(r[3]||"px")&&(e.style[u]=t,t=S.css(e,u)),Ye(0,t,s)}}}),S.cssHooks.marginLeft=Fe(y.reliableMarginLeft,function(e,t){if(t)return(parseFloat(We(e,"marginLeft"))||e.getBoundingClientRect().left-Me(e,{marginLeft:0},function(){return e.getBoundingClientRect().left}))+"px"}),S.each({margin:"",padding:"",border:"Width"},function(i,o){S.cssHooks[i+o]={expand:function(e){for(var t=0,n={},r="string"==typeof e?e.split(" "):[e];t<4;t++)n[i+ne[t]+o]=r[t]||r[t-2]||r[0];return n}},"margin"!==i&&(S.cssHooks[i+o].set=Ye)}),S.fn.extend({css:function(e,t){return $(this,function(e,t,n){var r,i,o={},a=0;if(Array.isArray(t)){for(r=Re(e),i=t.length;a<i;a++)o[t[a]]=S.css(e,t[a],!1,r);return o}return void 0!==n?S.style(e,t,n):S.css(e,t)},e,t,1<arguments.length)}}),((S.Tween=Ke).prototype={constructor:Ke,init:function(e,t,n,r,i,o){this.elem=e,this.prop=n,this.easing=i||S.easing._default,this.options=t,this.start=this.now=this.cur(),this.end=r,this.unit=o||(S.cssNumber[n]?"":"px")},cur:function(){var e=Ke.propHooks[this.prop];return e&&e.get?e.get(this):Ke.propHooks._default.get(this)},run:function(e){var t,n=Ke.propHooks[this.prop];return this.options.duration?this.pos=t=S.easing[this.easing](e,this.options.duration*e,0,1,this.options.duration):this.pos=t=e,this.now=(this.end-this.start)*t+this.start,this.options.step&&this.options.step.call(this.elem,this.now,this),n&&n.set?n.set(this):Ke.propHooks._default.set(this),this}}).init.prototype=Ke.prototype,(Ke.propHooks={_default:{get:function(e){var t;return 1!==e.elem.nodeType||null!=e.elem[e.prop]&&null==e.elem.style[e.prop]?e.elem[e.prop]:(t=S.css(e.elem,e.prop,""))&&"auto"!==t?t:0},set:function(e){S.fx.step[e.prop]?S.fx.step[e.prop](e):1!==e.elem.nodeType||!S.cssHooks[e.prop]&&null==e.elem.style[ze(e.prop)]?e.elem[e.prop]=e.now:S.style(e.elem,e.prop,e.now+e.unit)}}}).scrollTop=Ke.propHooks.scrollLeft={set:function(e){e.elem.nodeType&&e.elem.parentNode&&(e.elem[e.prop]=e.now)}},S.easing={linear:function(e){return e},swing:function(e){return.5-Math.cos(e*Math.PI)/2},_default:"swing"},S.fx=Ke.prototype.init,S.fx.step={};var Ze,et,tt,nt,rt=/^(?:toggle|show|hide)$/,it=/queueHooks$/;function ot(){et&&(!1===E.hidden&&C.requestAnimationFrame?C.requestAnimationFrame(ot):C.setTimeout(ot,S.fx.interval),S.fx.tick())}function at(){return C.setTimeout(function(){Ze=void 0}),Ze=Date.now()}function st(e,t){var n,r=0,i={height:e};for(t=t?1:0;r<4;r+=2-t)i["margin"+(n=ne[r])]=i["padding"+n]=e;return t&&(i.opacity=i.width=e),i}function ut(e,t,n){for(var r,i=(lt.tweeners[t]||[]).concat(lt.tweeners["*"]),o=0,a=i.length;o<a;o++)if(r=i[o].call(n,t,e))return r}function lt(o,e,t){var n,a,r=0,i=lt.prefilters.length,s=S.Deferred().always(function(){delete u.elem}),u=function(){if(a)return!1;for(var e=Ze||at(),t=Math.max(0,l.startTime+l.duration-e),n=1-(t/l.duration||0),r=0,i=l.tweens.length;r<i;r++)l.tweens[r].run(n);return s.notifyWith(o,[l,n,t]),n<1&&i?t:(i||s.notifyWith(o,[l,1,0]),s.resolveWith(o,[l]),!1)},l=s.promise({elem:o,props:S.extend({},e),opts:S.extend(!0,{specialEasing:{},easing:S.easing._default},t),originalProperties:e,originalOptions:t,startTime:Ze||at(),duration:t.duration,tweens:[],createTween:function(e,t){var n=S.Tween(o,l.opts,e,t,l.opts.specialEasing[e]||l.opts.easing);return l.tweens.push(n),n},stop:function(e){var t=0,n=e?l.tweens.length:0;if(a)return this;for(a=!0;t<n;t++)l.tweens[t].run(1);return e?(s.notifyWith(o,[l,1,0]),s.resolveWith(o,[l,e])):s.rejectWith(o,[l,e]),this}}),c=l.props;for(!function(e,t){var n,r,i,o,a;for(n in e)if(i=t[r=X(n)],o=e[n],Array.isArray(o)&&(i=o[1],o=e[n]=o[0]),n!==r&&(e[r]=o,delete e[n]),(a=S.cssHooks[r])&&"expand"in a)for(n in o=a.expand(o),delete e[r],o)n in e||(e[n]=o[n],t[n]=i);else t[r]=i}(c,l.opts.specialEasing);r<i;r++)if(n=lt.prefilters[r].call(l,o,c,l.opts))return m(n.stop)&&(S._queueHooks(l.elem,l.opts.queue).stop=n.stop.bind(n)),n;return S.map(c,ut,l),m(l.opts.start)&&l.opts.start.call(o,l),l.progress(l.opts.progress).done(l.opts.done,l.opts.complete).fail(l.opts.fail).always(l.opts.always),S.fx.timer(S.extend(u,{elem:o,anim:l,queue:l.opts.queue})),l}S.Animation=S.extend(lt,{tweeners:{"*":[function(e,t){var n=this.createTween(e,t);return se(n.elem,e,te.exec(t),n),n}]},tweener:function(e,t){m(e)?(t=e,e=["*"]):e=e.match(P);for(var n,r=0,i=e.length;r<i;r++)n=e[r],lt.tweeners[n]=lt.tweeners[n]||[],lt.tweeners[n].unshift(t)},prefilters:[function(e,t,n){var r,i,o,a,s,u,l,c,f="width"in t||"height"in t,p=this,d={},h=e.style,g=e.nodeType&&ae(e),v=Y.get(e,"fxshow");for(r in n.queue||(null==(a=S._queueHooks(e,"fx")).unqueued&&(a.unqueued=0,s=a.empty.fire,a.empty.fire=function(){a.unqueued||s()}),a.unqueued++,p.always(function(){p.always(function(){a.unqueued--,S.queue(e,"fx").length||a.empty.fire()})})),t)if(i=t[r],rt.test(i)){if(delete t[r],o=o||"toggle"===i,i===(g?"hide":"show")){if("show"!==i||!v||void 0===v[r])continue;g=!0}d[r]=v&&v[r]||S.style(e,r)}if((u=!S.isEmptyObject(t))||!S.isEmptyObject(d))for(r in f&&1===e.nodeType&&(n.overflow=[h.overflow,h.overflowX,h.overflowY],null==(l=v&&v.display)&&(l=Y.get(e,"display")),"none"===(c=S.css(e,"display"))&&(l?c=l:(le([e],!0),l=e.style.display||l,c=S.css(e,"display"),le([e]))),("inline"===c||"inline-block"===c&&null!=l)&&"none"===S.css(e,"float")&&(u||(p.done(function(){h.display=l}),null==l&&(c=h.display,l="none"===c?"":c)),h.display="inline-block")),n.overflow&&(h.overflow="hidden",p.always(function(){h.overflow=n.overflow[0],h.overflowX=n.overflow[1],h.overflowY=n.overflow[2]})),u=!1,d)u||(v?"hidden"in v&&(g=v.hidden):v=Y.access(e,"fxshow",{display:l}),o&&(v.hidden=!g),g&&le([e],!0),p.done(function(){for(r in g||le([e]),Y.remove(e,"fxshow"),d)S.style(e,r,d[r])})),u=ut(g?v[r]:0,r,p),r in v||(v[r]=u.start,g&&(u.end=u.start,u.start=0))}],prefilter:function(e,t){t?lt.prefilters.unshift(e):lt.prefilters.push(e)}}),S.speed=function(e,t,n){var r=e&&"object"==typeof e?S.extend({},e):{complete:n||!n&&t||m(e)&&e,duration:e,easing:n&&t||t&&!m(t)&&t};return S.fx.off?r.duration=0:"number"!=typeof r.duration&&(r.duration in S.fx.speeds?r.duration=S.fx.speeds[r.duration]:r.duration=S.fx.speeds._default),null!=r.queue&&!0!==r.queue||(r.queue="fx"),r.old=r.complete,r.complete=function(){m(r.old)&&r.old.call(this),r.queue&&S.dequeue(this,r.queue)},r},S.fn.extend({fadeTo:function(e,t,n,r){return this.filter(ae).css("opacity",0).show().end().animate({opacity:t},e,n,r)},animate:function(t,e,n,r){var i=S.isEmptyObject(t),o=S.speed(e,n,r),a=function(){var e=lt(this,S.extend({},t),o);(i||Y.get(this,"finish"))&&e.stop(!0)};return a.finish=a,i||!1===o.queue?this.each(a):this.queue(o.queue,a)},stop:function(i,e,o){var a=function(e){var t=e.stop;delete e.stop,t(o)};return"string"!=typeof i&&(o=e,e=i,i=void 0),e&&this.queue(i||"fx",[]),this.each(function(){var e=!0,t=null!=i&&i+"queueHooks",n=S.timers,r=Y.get(this);if(t)r[t]&&r[t].stop&&a(r[t]);else for(t in r)r[t]&&r[t].stop&&it.test(t)&&a(r[t]);for(t=n.length;t--;)n[t].elem!==this||null!=i&&n[t].queue!==i||(n[t].anim.stop(o),e=!1,n.splice(t,1));!e&&o||S.dequeue(this,i)})},finish:function(a){return!1!==a&&(a=a||"fx"),this.each(function(){var e,t=Y.get(this),n=t[a+"queue"],r=t[a+"queueHooks"],i=S.timers,o=n?n.length:0;for(t.finish=!0,S.queue(this,a,[]),r&&r.stop&&r.stop.call(this,!0),e=i.length;e--;)i[e].elem===this&&i[e].queue===a&&(i[e].anim.stop(!0),i.splice(e,1));for(e=0;e<o;e++)n[e]&&n[e].finish&&n[e].finish.call(this);delete t.finish})}}),S.each(["toggle","show","hide"],function(e,r){var i=S.fn[r];S.fn[r]=function(e,t,n){return null==e||"boolean"==typeof e?i.apply(this,arguments):this.animate(st(r,!0),e,t,n)}}),S.each({slideDown:st("show"),slideUp:st("hide"),slideToggle:st("toggle"),fadeIn:{opacity:"show"},fadeOut:{opacity:"hide"},fadeToggle:{opacity:"toggle"}},function(e,r){S.fn[e]=function(e,t,n){return this.animate(r,e,t,n)}}),S.timers=[],S.fx.tick=function(){var e,t=0,n=S.timers;for(Ze=Date.now();t<n.length;t++)(e=n[t])()||n[t]!==e||n.splice(t--,1);n.length||S.fx.stop(),Ze=void 0},S.fx.timer=function(e){S.timers.push(e),S.fx.start()},S.fx.interval=13,S.fx.start=function(){et||(et=!0,ot())},S.fx.stop=function(){et=null},S.fx.speeds={slow:600,fast:200,_default:400},S.fn.delay=function(r,e){return r=S.fx&&S.fx.speeds[r]||r,e=e||"fx",this.queue(e,function(e,t){var n=C.setTimeout(e,r);t.stop=function(){C.clearTimeout(n)}})},tt=E.createElement("input"),nt=E.createElement("select").appendChild(E.createElement("option")),tt.type="checkbox",y.checkOn=""!==tt.value,y.optSelected=nt.selected,(tt=E.createElement("input")).value="t",tt.type="radio",y.radioValue="t"===tt.value;var ct,ft=S.expr.attrHandle;S.fn.extend({attr:function(e,t){return $(this,S.attr,e,t,1<arguments.length)},removeAttr:function(e){return this.each(function(){S.removeAttr(this,e)})}}),S.extend({attr:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return"undefined"==typeof e.getAttribute?S.prop(e,t,n):(1===o&&S.isXMLDoc(e)||(i=S.attrHooks[t.toLowerCase()]||(S.expr.match.bool.test(t)?ct:void 0)),void 0!==n?null===n?void S.removeAttr(e,t):i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:(e.setAttribute(t,n+""),n):i&&"get"in i&&null!==(r=i.get(e,t))?r:null==(r=S.find.attr(e,t))?void 0:r)},attrHooks:{type:{set:function(e,t){if(!y.radioValue&&"radio"===t&&A(e,"input")){var n=e.value;return e.setAttribute("type",t),n&&(e.value=n),t}}}},removeAttr:function(e,t){var n,r=0,i=t&&t.match(P);if(i&&1===e.nodeType)while(n=i[r++])e.removeAttribute(n)}}),ct={set:function(e,t,n){return!1===t?S.removeAttr(e,n):e.setAttribute(n,n),n}},S.each(S.expr.match.bool.source.match(/\w+/g),function(e,t){var a=ft[t]||S.find.attr;ft[t]=function(e,t,n){var r,i,o=t.toLowerCase();return n||(i=ft[o],ft[o]=r,r=null!=a(e,t,n)?o:null,ft[o]=i),r}});var pt=/^(?:input|select|textarea|button)$/i,dt=/^(?:a|area)$/i;function ht(e){return(e.match(P)||[]).join(" ")}function gt(e){return e.getAttribute&&e.getAttribute("class")||""}function vt(e){return Array.isArray(e)?e:"string"==typeof e&&e.match(P)||[]}S.fn.extend({prop:function(e,t){return $(this,S.prop,e,t,1<arguments.length)},removeProp:function(e){return this.each(function(){delete this[S.propFix[e]||e]})}}),S.extend({prop:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return 1===o&&S.isXMLDoc(e)||(t=S.propFix[t]||t,i=S.propHooks[t]),void 0!==n?i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:e[t]=n:i&&"get"in i&&null!==(r=i.get(e,t))?r:e[t]},propHooks:{tabIndex:{get:function(e){var t=S.find.attr(e,"tabindex");return t?parseInt(t,10):pt.test(e.nodeName)||dt.test(e.nodeName)&&e.href?0:-1}}},propFix:{"for":"htmlFor","class":"className"}}),y.optSelected||(S.propHooks.selected={get:function(e){var t=e.parentNode;return t&&t.parentNode&&t.parentNode.selectedIndex,null},set:function(e){var t=e.parentNode;t&&(t.selectedIndex,t.parentNode&&t.parentNode.selectedIndex)}}),S.each(["tabIndex","readOnly","maxLength","cellSpacing","cellPadding","rowSpan","colSpan","useMap","frameBorder","contentEditable"],function(){S.propFix[this.toLowerCase()]=this}),S.fn.extend({addClass:function(t){var e,n,r,i,o,a,s,u=0;if(m(t))return this.each(function(e){S(this).addClass(t.call(this,e,gt(this)))});if((e=vt(t)).length)while(n=this[u++])if(i=gt(n),r=1===n.nodeType&&" "+ht(i)+" "){a=0;while(o=e[a++])r.indexOf(" "+o+" ")<0&&(r+=o+" ");i!==(s=ht(r))&&n.setAttribute("class",s)}return this},removeClass:function(t){var e,n,r,i,o,a,s,u=0;if(m(t))return this.each(function(e){S(this).removeClass(t.call(this,e,gt(this)))});if(!arguments.length)return this.attr("class","");if((e=vt(t)).length)while(n=this[u++])if(i=gt(n),r=1===n.nodeType&&" "+ht(i)+" "){a=0;while(o=e[a++])while(-1<r.indexOf(" "+o+" "))r=r.replace(" "+o+" "," ");i!==(s=ht(r))&&n.setAttribute("class",s)}return this},toggleClass:function(i,t){var o=typeof i,a="string"===o||Array.isArray(i);return"boolean"==typeof t&&a?t?this.addClass(i):this.removeClass(i):m(i)?this.each(function(e){S(this).toggleClass(i.call(this,e,gt(this),t),t)}):this.each(function(){var e,t,n,r;if(a){t=0,n=S(this),r=vt(i);while(e=r[t++])n.hasClass(e)?n.removeClass(e):n.addClass(e)}else void 0!==i&&"boolean"!==o||((e=gt(this))&&Y.set(this,"__className__",e),this.setAttribute&&this.setAttribute("class",e||!1===i?"":Y.get(this,"__className__")||""))})},hasClass:function(e){var t,n,r=0;t=" "+e+" ";while(n=this[r++])if(1===n.nodeType&&-1<(" "+ht(gt(n))+" ").indexOf(t))return!0;return!1}});var yt=/\r/g;S.fn.extend({val:function(n){var r,e,i,t=this[0];return arguments.length?(i=m(n),this.each(function(e){var t;1===this.nodeType&&(null==(t=i?n.call(this,e,S(this).val()):n)?t="":"number"==typeof t?t+="":Array.isArray(t)&&(t=S.map(t,function(e){return null==e?"":e+""})),(r=S.valHooks[this.type]||S.valHooks[this.nodeName.toLowerCase()])&&"set"in r&&void 0!==r.set(this,t,"value")||(this.value=t))})):t?(r=S.valHooks[t.type]||S.valHooks[t.nodeName.toLowerCase()])&&"get"in r&&void 0!==(e=r.get(t,"value"))?e:"string"==typeof(e=t.value)?e.replace(yt,""):null==e?"":e:void 0}}),S.extend({valHooks:{option:{get:function(e){var t=S.find.attr(e,"value");return null!=t?t:ht(S.text(e))}},select:{get:function(e){var t,n,r,i=e.options,o=e.selectedIndex,a="select-one"===e.type,s=a?null:[],u=a?o+1:i.length;for(r=o<0?u:a?o:0;r<u;r++)if(((n=i[r]).selected||r===o)&&!n.disabled&&(!n.parentNode.disabled||!A(n.parentNode,"optgroup"))){if(t=S(n).val(),a)return t;s.push(t)}return s},set:function(e,t){var n,r,i=e.options,o=S.makeArray(t),a=i.length;while(a--)((r=i[a]).selected=-1<S.inArray(S.valHooks.option.get(r),o))&&(n=!0);return n||(e.selectedIndex=-1),o}}}}),S.each(["radio","checkbox"],function(){S.valHooks[this]={set:function(e,t){if(Array.isArray(t))return e.checked=-1<S.inArray(S(e).val(),t)}},y.checkOn||(S.valHooks[this].get=function(e){return null===e.getAttribute("value")?"on":e.value})}),y.focusin="onfocusin"in C;var mt=/^(?:focusinfocus|focusoutblur)$/,xt=function(e){e.stopPropagation()};S.extend(S.event,{trigger:function(e,t,n,r){var i,o,a,s,u,l,c,f,p=[n||E],d=v.call(e,"type")?e.type:e,h=v.call(e,"namespace")?e.namespace.split("."):[];if(o=f=a=n=n||E,3!==n.nodeType&&8!==n.nodeType&&!mt.test(d+S.event.triggered)&&(-1<d.indexOf(".")&&(d=(h=d.split(".")).shift(),h.sort()),u=d.indexOf(":")<0&&"on"+d,(e=e[S.expando]?e:new S.Event(d,"object"==typeof e&&e)).isTrigger=r?2:3,e.namespace=h.join("."),e.rnamespace=e.namespace?new RegExp("(^|\\.)"+h.join("\\.(?:.*\\.|)")+"(\\.|$)"):null,e.result=void 0,e.target||(e.target=n),t=null==t?[e]:S.makeArray(t,[e]),c=S.event.special[d]||{},r||!c.trigger||!1!==c.trigger.apply(n,t))){if(!r&&!c.noBubble&&!x(n)){for(s=c.delegateType||d,mt.test(s+d)||(o=o.parentNode);o;o=o.parentNode)p.push(o),a=o;a===(n.ownerDocument||E)&&p.push(a.defaultView||a.parentWindow||C)}i=0;while((o=p[i++])&&!e.isPropagationStopped())f=o,e.type=1<i?s:c.bindType||d,(l=(Y.get(o,"events")||Object.create(null))[e.type]&&Y.get(o,"handle"))&&l.apply(o,t),(l=u&&o[u])&&l.apply&&V(o)&&(e.result=l.apply(o,t),!1===e.result&&e.preventDefault());return e.type=d,r||e.isDefaultPrevented()||c._default&&!1!==c._default.apply(p.pop(),t)||!V(n)||u&&m(n[d])&&!x(n)&&((a=n[u])&&(n[u]=null),S.event.triggered=d,e.isPropagationStopped()&&f.addEventListener(d,xt),n[d](),e.isPropagationStopped()&&f.removeEventListener(d,xt),S.event.triggered=void 0,a&&(n[u]=a)),e.result}},simulate:function(e,t,n){var r=S.extend(new S.Event,n,{type:e,isSimulated:!0});S.event.trigger(r,null,t)}}),S.fn.extend({trigger:function(e,t){return this.each(function(){S.event.trigger(e,t,this)})},triggerHandler:function(e,t){var n=this[0];if(n)return S.event.trigger(e,t,n,!0)}}),y.focusin||S.each({focus:"focusin",blur:"focusout"},function(n,r){var i=function(e){S.event.simulate(r,e.target,S.event.fix(e))};S.event.special[r]={setup:function(){var e=this.ownerDocument||this.document||this,t=Y.access(e,r);t||e.addEventListener(n,i,!0),Y.access(e,r,(t||0)+1)},teardown:function(){var e=this.ownerDocument||this.document||this,t=Y.access(e,r)-1;t?Y.access(e,r,t):(e.removeEventListener(n,i,!0),Y.remove(e,r))}}});var bt=C.location,wt={guid:Date.now()},Tt=/\?/;S.parseXML=function(e){var t,n;if(!e||"string"!=typeof e)return null;try{t=(new C.DOMParser).parseFromString(e,"text/xml")}catch(e){}return n=t&&t.getElementsByTagName("parsererror")[0],t&&!n||S.error("Invalid XML: "+(n?S.map(n.childNodes,function(e){return e.textContent}).join("\n"):e)),t};var Ct=/\[\]$/,Et=/\r?\n/g,St=/^(?:submit|button|image|reset|file)$/i,kt=/^(?:input|select|textarea|keygen)/i;function At(n,e,r,i){var t;if(Array.isArray(e))S.each(e,function(e,t){r||Ct.test(n)?i(n,t):At(n+"["+("object"==typeof t&&null!=t?e:"")+"]",t,r,i)});else if(r||"object"!==w(e))i(n,e);else for(t in e)At(n+"["+t+"]",e[t],r,i)}S.param=function(e,t){var n,r=[],i=function(e,t){var n=m(t)?t():t;r[r.length]=encodeURIComponent(e)+"="+encodeURIComponent(null==n?"":n)};if(null==e)return"";if(Array.isArray(e)||e.jquery&&!S.isPlainObject(e))S.each(e,function(){i(this.name,this.value)});else for(n in e)At(n,e[n],t,i);return r.join("&")},S.fn.extend({serialize:function(){return S.param(this.serializeArray())},serializeArray:function(){return this.map(function(){var e=S.prop(this,"elements");return e?S.makeArray(e):this}).filter(function(){var e=this.type;return this.name&&!S(this).is(":disabled")&&kt.test(this.nodeName)&&!St.test(e)&&(this.checked||!pe.test(e))}).map(function(e,t){var n=S(this).val();return null==n?null:Array.isArray(n)?S.map(n,function(e){return{name:t.name,value:e.replace(Et,"\r\n")}}):{name:t.name,value:n.replace(Et,"\r\n")}}).get()}});var Nt=/%20/g,jt=/#.*$/,Dt=/([?&])_=[^&]*/,qt=/^(.*?):[ \t]*([^\r\n]*)$/gm,Lt=/^(?:GET|HEAD)$/,Ht=/^\/\//,Ot={},Pt={},Rt="*/".concat("*"),Mt=E.createElement("a");function It(o){return function(e,t){"string"!=typeof e&&(t=e,e="*");var n,r=0,i=e.toLowerCase().match(P)||[];if(m(t))while(n=i[r++])"+"===n[0]?(n=n.slice(1)||"*",(o[n]=o[n]||[]).unshift(t)):(o[n]=o[n]||[]).push(t)}}function Wt(t,i,o,a){var s={},u=t===Pt;function l(e){var r;return s[e]=!0,S.each(t[e]||[],function(e,t){var n=t(i,o,a);return"string"!=typeof n||u||s[n]?u?!(r=n):void 0:(i.dataTypes.unshift(n),l(n),!1)}),r}return l(i.dataTypes[0])||!s["*"]&&l("*")}function Ft(e,t){var n,r,i=S.ajaxSettings.flatOptions||{};for(n in t)void 0!==t[n]&&((i[n]?e:r||(r={}))[n]=t[n]);return r&&S.extend(!0,e,r),e}Mt.href=bt.href,S.extend({active:0,lastModified:{},etag:{},ajaxSettings:{url:bt.href,type:"GET",isLocal:/^(?:about|app|app-storage|.+-extension|file|res|widget):$/.test(bt.protocol),global:!0,processData:!0,async:!0,contentType:"application/x-www-form-urlencoded; charset=UTF-8",accepts:{"*":Rt,text:"text/plain",html:"text/html",xml:"application/xml, text/xml",json:"application/json, text/javascript"},contents:{xml:/\bxml\b/,html:/\bhtml/,json:/\bjson\b/},responseFields:{xml:"responseXML",text:"responseText",json:"responseJSON"},converters:{"* text":String,"text html":!0,"text json":JSON.parse,"text xml":S.parseXML},flatOptions:{url:!0,context:!0}},ajaxSetup:function(e,t){return t?Ft(Ft(e,S.ajaxSettings),t):Ft(S.ajaxSettings,e)},ajaxPrefilter:It(Ot),ajaxTransport:It(Pt),ajax:function(e,t){"object"==typeof e&&(t=e,e=void 0),t=t||{};var c,f,p,n,d,r,h,g,i,o,v=S.ajaxSetup({},t),y=v.context||v,m=v.context&&(y.nodeType||y.jquery)?S(y):S.event,x=S.Deferred(),b=S.Callbacks("once memory"),w=v.statusCode||{},a={},s={},u="canceled",T={readyState:0,getResponseHeader:function(e){var t;if(h){if(!n){n={};while(t=qt.exec(p))n[t[1].toLowerCase()+" "]=(n[t[1].toLowerCase()+" "]||[]).concat(t[2])}t=n[e.toLowerCase()+" "]}return null==t?null:t.join(", ")},getAllResponseHeaders:function(){return h?p:null},setRequestHeader:function(e,t){return null==h&&(e=s[e.toLowerCase()]=s[e.toLowerCase()]||e,a[e]=t),this},overrideMimeType:function(e){return null==h&&(v.mimeType=e),this},statusCode:function(e){var t;if(e)if(h)T.always(e[T.status]);else for(t in e)w[t]=[w[t],e[t]];return this},abort:function(e){var t=e||u;return c&&c.abort(t),l(0,t),this}};if(x.promise(T),v.url=((e||v.url||bt.href)+"").replace(Ht,bt.protocol+"//"),v.type=t.method||t.type||v.method||v.type,v.dataTypes=(v.dataType||"*").toLowerCase().match(P)||[""],null==v.crossDomain){r=E.createElement("a");try{r.href=v.url,r.href=r.href,v.crossDomain=Mt.protocol+"//"+Mt.host!=r.protocol+"//"+r.host}catch(e){v.crossDomain=!0}}if(v.data&&v.processData&&"string"!=typeof v.data&&(v.data=S.param(v.data,v.traditional)),Wt(Ot,v,t,T),h)return T;for(i in(g=S.event&&v.global)&&0==S.active++&&S.event.trigger("ajaxStart"),v.type=v.type.toUpperCase(),v.hasContent=!Lt.test(v.type),f=v.url.replace(jt,""),v.hasContent?v.data&&v.processData&&0===(v.contentType||"").indexOf("application/x-www-form-urlencoded")&&(v.data=v.data.replace(Nt,"+")):(o=v.url.slice(f.length),v.data&&(v.processData||"string"==typeof v.data)&&(f+=(Tt.test(f)?"&":"?")+v.data,delete v.data),!1===v.cache&&(f=f.replace(Dt,"$1"),o=(Tt.test(f)?"&":"?")+"_="+wt.guid+++o),v.url=f+o),v.ifModified&&(S.lastModified[f]&&T.setRequestHeader("If-Modified-Since",S.lastModified[f]),S.etag[f]&&T.setRequestHeader("If-None-Match",S.etag[f])),(v.data&&v.hasContent&&!1!==v.contentType||t.contentType)&&T.setRequestHeader("Content-Type",v.contentType),T.setRequestHeader("Accept",v.dataTypes[0]&&v.accepts[v.dataTypes[0]]?v.accepts[v.dataTypes[0]]+("*"!==v.dataTypes[0]?", "+Rt+"; q=0.01":""):v.accepts["*"]),v.headers)T.setRequestHeader(i,v.headers[i]);if(v.beforeSend&&(!1===v.beforeSend.call(y,T,v)||h))return T.abort();if(u="abort",b.add(v.complete),T.done(v.success),T.fail(v.error),c=Wt(Pt,v,t,T)){if(T.readyState=1,g&&m.trigger("ajaxSend",[T,v]),h)return T;v.async&&0<v.timeout&&(d=C.setTimeout(function(){T.abort("timeout")},v.timeout));try{h=!1,c.send(a,l)}catch(e){if(h)throw e;l(-1,e)}}else l(-1,"No Transport");function l(e,t,n,r){var i,o,a,s,u,l=t;h||(h=!0,d&&C.clearTimeout(d),c=void 0,p=r||"",T.readyState=0<e?4:0,i=200<=e&&e<300||304===e,n&&(s=function(e,t,n){var r,i,o,a,s=e.contents,u=e.dataTypes;while("*"===u[0])u.shift(),void 0===r&&(r=e.mimeType||t.getResponseHeader("Content-Type"));if(r)for(i in s)if(s[i]&&s[i].test(r)){u.unshift(i);break}if(u[0]in n)o=u[0];else{for(i in n){if(!u[0]||e.converters[i+" "+u[0]]){o=i;break}a||(a=i)}o=o||a}if(o)return o!==u[0]&&u.unshift(o),n[o]}(v,T,n)),!i&&-1<S.inArray("script",v.dataTypes)&&S.inArray("json",v.dataTypes)<0&&(v.converters["text script"]=function(){}),s=function(e,t,n,r){var i,o,a,s,u,l={},c=e.dataTypes.slice();if(c[1])for(a in e.converters)l[a.toLowerCase()]=e.converters[a];o=c.shift();while(o)if(e.responseFields[o]&&(n[e.responseFields[o]]=t),!u&&r&&e.dataFilter&&(t=e.dataFilter(t,e.dataType)),u=o,o=c.shift())if("*"===o)o=u;else if("*"!==u&&u!==o){if(!(a=l[u+" "+o]||l["* "+o]))for(i in l)if((s=i.split(" "))[1]===o&&(a=l[u+" "+s[0]]||l["* "+s[0]])){!0===a?a=l[i]:!0!==l[i]&&(o=s[0],c.unshift(s[1]));break}if(!0!==a)if(a&&e["throws"])t=a(t);else try{t=a(t)}catch(e){return{state:"parsererror",error:a?e:"No conversion from "+u+" to "+o}}}return{state:"success",data:t}}(v,s,T,i),i?(v.ifModified&&((u=T.getResponseHeader("Last-Modified"))&&(S.lastModified[f]=u),(u=T.getResponseHeader("etag"))&&(S.etag[f]=u)),204===e||"HEAD"===v.type?l="nocontent":304===e?l="notmodified":(l=s.state,o=s.data,i=!(a=s.error))):(a=l,!e&&l||(l="error",e<0&&(e=0))),T.status=e,T.statusText=(t||l)+"",i?x.resolveWith(y,[o,l,T]):x.rejectWith(y,[T,l,a]),T.statusCode(w),w=void 0,g&&m.trigger(i?"ajaxSuccess":"ajaxError",[T,v,i?o:a]),b.fireWith(y,[T,l]),g&&(m.trigger("ajaxComplete",[T,v]),--S.active||S.event.trigger("ajaxStop")))}return T},getJSON:function(e,t,n){return S.get(e,t,n,"json")},getScript:function(e,t){return S.get(e,void 0,t,"script")}}),S.each(["get","post"],function(e,i){S[i]=function(e,t,n,r){return m(t)&&(r=r||n,n=t,t=void 0),S.ajax(S.extend({url:e,type:i,dataType:r,data:t,success:n},S.isPlainObject(e)&&e))}}),S.ajaxPrefilter(function(e){var t;for(t in e.headers)"content-type"===t.toLowerCase()&&(e.contentType=e.headers[t]||"")}),S._evalUrl=function(e,t,n){return S.ajax({url:e,type:"GET",dataType:"script",cache:!0,async:!1,global:!1,converters:{"text script":function(){}},dataFilter:function(e){S.globalEval(e,t,n)}})},S.fn.extend({wrapAll:function(e){var t;return this[0]&&(m(e)&&(e=e.call(this[0])),t=S(e,this[0].ownerDocument).eq(0).clone(!0),this[0].parentNode&&t.insertBefore(this[0]),t.map(function(){var e=this;while(e.firstElementChild)e=e.firstElementChild;return e}).append(this)),this},wrapInner:function(n){return m(n)?this.each(function(e){S(this).wrapInner(n.call(this,e))}):this.each(function(){var e=S(this),t=e.contents();t.length?t.wrapAll(n):e.append(n)})},wrap:function(t){var n=m(t);return this.each(function(e){S(this).wrapAll(n?t.call(this,e):t)})},unwrap:function(e){return this.parent(e).not("body").each(function(){S(this).replaceWith(this.childNodes)}),this}}),S.expr.pseudos.hidden=function(e){return!S.expr.pseudos.visible(e)},S.expr.pseudos.visible=function(e){return!!(e.offsetWidth||e.offsetHeight||e.getClientRects().length)},S.ajaxSettings.xhr=function(){try{return new C.XMLHttpRequest}catch(e){}};var Bt={0:200,1223:204},$t=S.ajaxSettings.xhr();y.cors=!!$t&&"withCredentials"in $t,y.ajax=$t=!!$t,S.ajaxTransport(function(i){var o,a;if(y.cors||$t&&!i.crossDomain)return{send:function(e,t){var n,r=i.xhr();if(r.open(i.type,i.url,i.async,i.username,i.password),i.xhrFields)for(n in i.xhrFields)r[n]=i.xhrFields[n];for(n in i.mimeType&&r.overrideMimeType&&r.overrideMimeType(i.mimeType),i.crossDomain||e["X-Requested-With"]||(e["X-Requested-With"]="XMLHttpRequest"),e)r.setRequestHeader(n,e[n]);o=function(e){return function(){o&&(o=a=r.onload=r.onerror=r.onabort=r.ontimeout=r.onreadystatechange=null,"abort"===e?r.abort():"error"===e?"number"!=typeof r.status?t(0,"error"):t(r.status,r.statusText):t(Bt[r.status]||r.status,r.statusText,"text"!==(r.responseType||"text")||"string"!=typeof r.responseText?{binary:r.response}:{text:r.responseText},r.getAllResponseHeaders()))}},r.onload=o(),a=r.onerror=r.ontimeout=o("error"),void 0!==r.onabort?r.onabort=a:r.onreadystatechange=function(){4===r.readyState&&C.setTimeout(function(){o&&a()})},o=o("abort");try{r.send(i.hasContent&&i.data||null)}catch(e){if(o)throw e}},abort:function(){o&&o()}}}),S.ajaxPrefilter(function(e){e.crossDomain&&(e.contents.script=!1)}),S.ajaxSetup({accepts:{script:"text/javascript, application/javascript, application/ecmascript, application/x-ecmascript"},contents:{script:/\b(?:java|ecma)script\b/},converters:{"text script":function(e){return S.globalEval(e),e}}}),S.ajaxPrefilter("script",function(e){void 0===e.cache&&(e.cache=!1),e.crossDomain&&(e.type="GET")}),S.ajaxTransport("script",function(n){var r,i;if(n.crossDomain||n.scriptAttrs)return{send:function(e,t){r=S("<script>").attr(n.scriptAttrs||{}).prop({charset:n.scriptCharset,src:n.url}).on("load error",i=function(e){r.remove(),i=null,e&&t("error"===e.type?404:200,e.type)}),E.head.appendChild(r[0])},abort:function(){i&&i()}}});var _t,zt=[],Ut=/(=)\?(?=&|$)|\?\?/;S.ajaxSetup({jsonp:"callback",jsonpCallback:function(){var e=zt.pop()||S.expando+"_"+wt.guid++;return this[e]=!0,e}}),S.ajaxPrefilter("json jsonp",function(e,t,n){var r,i,o,a=!1!==e.jsonp&&(Ut.test(e.url)?"url":"string"==typeof e.data&&0===(e.contentType||"").indexOf("application/x-www-form-urlencoded")&&Ut.test(e.data)&&"data");if(a||"jsonp"===e.dataTypes[0])return r=e.jsonpCallback=m(e.jsonpCallback)?e.jsonpCallback():e.jsonpCallback,a?e[a]=e[a].replace(Ut,"$1"+r):!1!==e.jsonp&&(e.url+=(Tt.test(e.url)?"&":"?")+e.jsonp+"="+r),e.converters["script json"]=function(){return o||S.error(r+" was not called"),o[0]},e.dataTypes[0]="json",i=C[r],C[r]=function(){o=arguments},n.always(function(){void 0===i?S(C).removeProp(r):C[r]=i,e[r]&&(e.jsonpCallback=t.jsonpCallback,zt.push(r)),o&&m(i)&&i(o[0]),o=i=void 0}),"script"}),y.createHTMLDocument=((_t=E.implementation.createHTMLDocument("").body).innerHTML="<form></form><form></form>",2===_t.childNodes.length),S.parseHTML=function(e,t,n){return"string"!=typeof e?[]:("boolean"==typeof t&&(n=t,t=!1),t||(y.createHTMLDocument?((r=(t=E.implementation.createHTMLDocument("")).createElement("base")).href=E.location.href,t.head.appendChild(r)):t=E),o=!n&&[],(i=N.exec(e))?[t.createElement(i[1])]:(i=xe([e],t,o),o&&o.length&&S(o).remove(),S.merge([],i.childNodes)));var r,i,o},S.fn.load=function(e,t,n){var r,i,o,a=this,s=e.indexOf(" ");return-1<s&&(r=ht(e.slice(s)),e=e.slice(0,s)),m(t)?(n=t,t=void 0):t&&"object"==typeof t&&(i="POST"),0<a.length&&S.ajax({url:e,type:i||"GET",dataType:"html",data:t}).done(function(e){o=arguments,a.html(r?S("<div>").append(S.parseHTML(e)).find(r):e)}).always(n&&function(e,t){a.each(function(){n.apply(this,o||[e.responseText,t,e])})}),this},S.expr.pseudos.animated=function(t){return S.grep(S.timers,function(e){return t===e.elem}).length},S.offset={setOffset:function(e,t,n){var r,i,o,a,s,u,l=S.css(e,"position"),c=S(e),f={};"static"===l&&(e.style.position="relative"),s=c.offset(),o=S.css(e,"top"),u=S.css(e,"left"),("absolute"===l||"fixed"===l)&&-1<(o+u).indexOf("auto")?(a=(r=c.position()).top,i=r.left):(a=parseFloat(o)||0,i=parseFloat(u)||0),m(t)&&(t=t.call(e,n,S.extend({},s))),null!=t.top&&(f.top=t.top-s.top+a),null!=t.left&&(f.left=t.left-s.left+i),"using"in t?t.using.call(e,f):c.css(f)}},S.fn.extend({offset:function(t){if(arguments.length)return void 0===t?this:this.each(function(e){S.offset.setOffset(this,t,e)});var e,n,r=this[0];return r?r.getClientRects().length?(e=r.getBoundingClientRect(),n=r.ownerDocument.defaultView,{top:e.top+n.pageYOffset,left:e.left+n.pageXOffset}):{top:0,left:0}:void 0},position:function(){if(this[0]){var e,t,n,r=this[0],i={top:0,left:0};if("fixed"===S.css(r,"position"))t=r.getBoundingClientRect();else{t=this.offset(),n=r.ownerDocument,e=r.offsetParent||n.documentElement;while(e&&(e===n.body||e===n.documentElement)&&"static"===S.css(e,"position"))e=e.parentNode;e&&e!==r&&1===e.nodeType&&((i=S(e).offset()).top+=S.css(e,"borderTopWidth",!0),i.left+=S.css(e,"borderLeftWidth",!0))}return{top:t.top-i.top-S.css(r,"marginTop",!0),left:t.left-i.left-S.css(r,"marginLeft",!0)}}},offsetParent:function(){return this.map(function(){var e=this.offsetParent;while(e&&"static"===S.css(e,"position"))e=e.offsetParent;return e||re})}}),S.each({scrollLeft:"pageXOffset",scrollTop:"pageYOffset"},function(t,i){var o="pageYOffset"===i;S.fn[t]=function(e){return $(this,function(e,t,n){var r;if(x(e)?r=e:9===e.nodeType&&(r=e.defaultView),void 0===n)return r?r[i]:e[t];r?r.scrollTo(o?r.pageXOffset:n,o?n:r.pageYOffset):e[t]=n},t,e,arguments.length)}}),S.each(["top","left"],function(e,n){S.cssHooks[n]=Fe(y.pixelPosition,function(e,t){if(t)return t=We(e,n),Pe.test(t)?S(e).position()[n]+"px":t})}),S.each({Height:"height",Width:"width"},function(a,s){S.each({padding:"inner"+a,content:s,"":"outer"+a},function(r,o){S.fn[o]=function(e,t){var n=arguments.length&&(r||"boolean"!=typeof e),i=r||(!0===e||!0===t?"margin":"border");return $(this,function(e,t,n){var r;return x(e)?0===o.indexOf("outer")?e["inner"+a]:e.document.documentElement["client"+a]:9===e.nodeType?(r=e.documentElement,Math.max(e.body["scroll"+a],r["scroll"+a],e.body["offset"+a],r["offset"+a],r["client"+a])):void 0===n?S.css(e,t,i):S.style(e,t,n,i)},s,n?e:void 0,n)}})}),S.each(["ajaxStart","ajaxStop","ajaxComplete","ajaxError","ajaxSuccess","ajaxSend"],function(e,t){S.fn[t]=function(e){return this.on(t,e)}}),S.fn.extend({bind:function(e,t,n){return this.on(e,null,t,n)},unbind:function(e,t){return this.off(e,null,t)},delegate:function(e,t,n,r){return this.on(t,e,n,r)},undelegate:function(e,t,n){return 1===arguments.length?this.off(e,"**"):this.off(t,e||"**",n)},hover:function(e,t){return this.mouseenter(e).mouseleave(t||e)}}),S.each("blur focus focusin focusout resize scroll click dblclick mousedown mouseup mousemove mouseover mouseout mouseenter mouseleave change select submit keydown keypress keyup contextmenu".split(" "),function(e,n){S.fn[n]=function(e,t){return 0<arguments.length?this.on(n,null,e,t):this.trigger(n)}});var Xt=/^[\s\uFEFF\xA0]+|[\s\uFEFF\xA0]+$/g;S.proxy=function(e,t){var n,r,i;if("string"==typeof t&&(n=e[t],t=e,e=n),m(e))return r=s.call(arguments,2),(i=function(){return e.apply(t||this,r.concat(s.call(arguments)))}).guid=e.guid=e.guid||S.guid++,i},S.holdReady=function(e){e?S.readyWait++:S.ready(!0)},S.isArray=Array.isArray,S.parseJSON=JSON.parse,S.nodeName=A,S.isFunction=m,S.isWindow=x,S.camelCase=X,S.type=w,S.now=Date.now,S.isNumeric=function(e){var t=S.type(e);return("number"===t||"string"===t)&&!isNaN(e-parseFloat(e))},S.trim=function(e){return null==e?"":(e+"").replace(Xt,"")},"function"==typeof define&&define.amd&&define("jquery",[],function(){return S});var Vt=C.jQuery,Gt=C.$;return S.noConflict=function(e){return C.$===S&&(C.$=Gt),e&&C.jQuery===S&&(C.jQuery=Vt),S},"undefined"==typeof e&&(C.jQuery=C.$=S),S});
</script>
<meta name="viewport" content="width=device-width, initial-scale=1" />
<style type="text/css">html{font-family:sans-serif;-webkit-text-size-adjust:100%;-ms-text-size-adjust:100%}body{margin:0}article,aside,details,figcaption,figure,footer,header,hgroup,main,menu,nav,section,summary{display:block}audio,canvas,progress,video{display:inline-block;vertical-align:baseline}audio:not([controls]){display:none;height:0}[hidden],template{display:none}a{background-color:transparent}a:active,a:hover{outline:0}abbr[title]{border-bottom:1px dotted}b,strong{font-weight:700}dfn{font-style:italic}h1{margin:.67em 0;font-size:2em}mark{color:#000;background:#ff0}small{font-size:80%}sub,sup{position:relative;font-size:75%;line-height:0;vertical-align:baseline}sup{top:-.5em}sub{bottom:-.25em}img{border:0}svg:not(:root){overflow:hidden}figure{margin:1em 40px}hr{height:0;-webkit-box-sizing:content-box;-moz-box-sizing:content-box;box-sizing:content-box}pre{overflow:auto}code,kbd,pre,samp{font-family:monospace,monospace;font-size:1em}button,input,optgroup,select,textarea{margin:0;font:inherit;color:inherit}button{overflow:visible}button,select{text-transform:none}button,html input[type=button],input[type=reset],input[type=submit]{-webkit-appearance:button;cursor:pointer}button[disabled],html input[disabled]{cursor:default}button::-moz-focus-inner,input::-moz-focus-inner{padding:0;border:0}input{line-height:normal}input[type=checkbox],input[type=radio]{-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box;padding:0}input[type=number]::-webkit-inner-spin-button,input[type=number]::-webkit-outer-spin-button{height:auto}input[type=search]{-webkit-box-sizing:content-box;-moz-box-sizing:content-box;box-sizing:content-box;-webkit-appearance:textfield}input[type=search]::-webkit-search-cancel-button,input[type=search]::-webkit-search-decoration{-webkit-appearance:none}fieldset{padding:.35em .625em .75em;margin:0 2px;border:1px solid silver}legend{padding:0;border:0}textarea{overflow:auto}optgroup{font-weight:700}table{border-spacing:0;border-collapse:collapse}td,th{padding:0}@media print{*,:after,:before{color:#000!important;text-shadow:none!important;background:0 0!important;-webkit-box-shadow:none!important;box-shadow:none!important}a,a:visited{text-decoration:underline}a[href]:after{content:" (" attr(href) ")"}abbr[title]:after{content:" (" attr(title) ")"}a[href^="javascript:"]:after,a[href^="#"]:after{content:""}blockquote,pre{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}img,tr{page-break-inside:avoid}img{max-width:100%!important}h2,h3,p{orphans:3;widows:3}h2,h3{page-break-after:avoid}.navbar{display:none}.btn>.caret,.dropup>.btn>.caret{border-top-color:#000!important}.label{border:1px solid #000}.table{border-collapse:collapse!important}.table td,.table th{background-color:#fff!important}.table-bordered td,.table-bordered th{border:1px solid #ddd!important}}@font-face{font-family:'Glyphicons Halflings';src:url(data:application/vnd.ms-fontobject;base64,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);src:url(data:application/vnd.ms-fontobject;base64,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) format('embedded-opentype'),url(data:font/woff;base64,d09GRgABAAAAAFuAAA8AAAAAsVwAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAABGRlRNAAABWAAAABwAAAAcbSqX3EdERUYAAAF0AAAAHwAAACABRAAET1MvMgAAAZQAAABFAAAAYGe5a4ljbWFwAAAB3AAAAsAAAAZy2q3jgWN2dCAAAAScAAAABAAAAAQAKAL4Z2FzcAAABKAAAAAIAAAACP//AANnbHlmAAAEqAAATRcAAJSkfV3Cb2hlYWQAAFHAAAAANAAAADYFTS/YaGhlYQAAUfQAAAAcAAAAJApEBBFobXR4AABSEAAAAU8AAAN00scgYGxvY2EAAFNgAAACJwAAAjBv+5XObWF4cAAAVYgAAAAgAAAAIAFqANhuYW1lAABVqAAAAZ4AAAOisyygm3Bvc3QAAFdIAAAELQAACtG6o+U1d2ViZgAAW3gAAAAGAAAABsMYVFAAAAABAAAAAMw9os8AAAAA0HaBdQAAAADQdnOXeNpjYGRgYOADYgkGEGBiYGRgZBQDkixgHgMABUgASgB42mNgZulmnMDAysDCzMN0gYGBIQpCMy5hMGLaAeQDpRCACYkd6h3ux+DAoPD/P/OB/wJAdSIM1UBhRiQlCgyMADGWCwwAAAB42u2UP2hTQRzHf5ekaVPExv6JjW3fvTQ0sa3QLA5xylBLgyBx0gzSWEUaXbIoBBQyCQGHLqXUqYNdtIIgIg5FHJxEtwqtpbnfaV1E1KFaSvX5vVwGEbW6OPngk8/vvXfv7pt3v4SImojIDw6BViKxRgIVBaZwVdSv+xvXA+Iuzqcog2cOkkvDNE8Lbqs74k64i+5Sf3u8Z2AnIRLbyVCyTflVSEXVoEqrrMqrgiqqsqqqWQ5xlAc5zWOc5TwXucxVnuE5HdQhHdFRHdNJndZZndeFLc/zsKJLQ/WV6BcrCdWkwspVKZVROaw0qUqqoqZZcJhdTnGGxznHBS5xhad5VhNWCuturBTXKZ3RObuS98pb9c57k6ql9rp2v1as5deb1r6s9q1GV2IrHSt73T631424YXzjgPwqt+Rn+VG+lRvyirwsS/KCPCfPytPypDwhj8mjctRZd9acF86y89x55jxxHjkPnXstXfbt/pNjj/nwXW+cHa6/SYvZ7yEwbDYazDcIgoUGzY3h2HtqgUcs1AFPWKgTXrRQF7xkoQhRf7uF9hPFeyzUTTSwY6EoUUJY6AC8bSGMS4Ys1Au3WaiPSGGsMtkdGH2rzJgYHAaYjxIwQqtB1CnYkEZ9BM6ALOpROAfyqI/DBQudgidBETXuqRIooz4DV0AV9UV4GsyivkTEyMMmw1UYGdhkuAYjA5sMGMvIwCbDDRgZeAz1TXgcmDy3YeRhk+cOjCxsMjyAkYFNhscwMrDJ8BQ2886gXoaRhedQvyTSkDZ7uA6HLLQBI5vGntAbGHugTc53cMxC7+E4SKL+ACOzNpk3YWTWJid+iRo5NXIKM3fBItAPW55FdJLY3FeHBDr90606JCIU9Jk+Ms3/Y/8L8jUq3y79bJ/0/+ROoP4v9v/4/mj+i7HBXUd0/elU6IHfHt8Aj9EPGAAoAvgAAAAB//8AAnjaxb0JfBvVtTA+dxaN1hltI1m2ZVuSJVneLVlSHCdy9oTEWchqtrBEJRAgCYEsQNhC2EsbWmpI2dqkQBoSYgKlpaQthVL0yusrpW77aEubfq/ly+ujvJampSTW5Dvnzmi1E+jr//3+Xmbu3Llz77nnbuece865DMu0MAy5jGtiOEZkOp8lTNeUwyLP/DH+rEH41ZTDHAtB5lkOowWMPiwayNiUwwTjE46AI5xwhFrINPXYn/7ENY0dbWHfZAiTZbL8ID/InAd5xz2NpIH4STpDGonHIJNE3OP1KG4ISaSNeBuITAyRLgIxoiEUhFAnmUpEiXSRSGqAQEw0kuyFUIb0k2gnGSApyBFi0il2SI5YLGb5MdFjXCey4mNHzQ7WwLGEdZiPPgYR64we8THZHAt+wnT84D/x8YTpGPgheKH4CMEDVF9xBOIeP3EbQgGH29BGgpGkIxCMTCW9qUTA0Zsir+QUP1mt+P2KusevwIO6Bx/Iaj8/OD5O0VNrZW2EsqZBWbO1skRiEKE0DdlKKaSVO5VAuRpqk8VQJAqY7ydxaK44YJvrO2EWjOoDBoFYzQbDNkON+UbiKoRkywMWWf1j4bEY2iIY1AeMgvmEz/kVo9v4FSc/aMZMrFbjl4zWLL0+Y5FlyzNlEVYDudJohg8gPUP7kcB/mn+G6cd+5PV4Q72dXCgocWJADBgUuDTwiXiGSyZo14HOEQ2lE6k0XDIEusexDzZOMXwt1Dutz+tqmxTvlskNWXXUQIbhaurum9GrePqm9Yaeabjkiqf+bUvzDOvb2Y1E+EX2DnemcTP/zLcuu7xjQXdAtjR0Lo5n4/Hs/GtntMlysHt+29NXbH6se//WbFcyu+r28H0MwzI30DYeYTLMXIA2EG8QlHpAsyS0EfEToR0a3utIxFPJ3kiIHCCrZ66b0e2xEmL1dM9YN/MwS5p01N5jMX/BLKt/1R83l0LyC29M6+iYxo/UNg/EF7c2WyyW5tYl8WnhWg2/hyySbD5UhnDyS7OcU0dnrFw+DfGdI7v4QfYIIzOMq9hFtY55gmvC7jZ2FK7sEdrn6IXBuucYhjsGdQ8z0yEbWkkczjjsE5hNAIZrPx2zOLZDmKNXcXtg7EMqidAEEWg+SJCBBNwxvxJfc/bZa+KKf+xoKZybnq5vaqpPTye7CiF+ZFjxZ8/7Qij0hfOG/cowPA1rT1l4ymWnrKmxxqfErTVrpgwPlz1kC+Oy8NMDz6c+IO38K/x0xkPnLW8Kx6qGAoQdL+TD9V9rb+/ctn//trxz8dUrZrD/zk/ferF0cNt1BzctmX2FZPXt/jnFCQNz4Ah/iKllGiCMs1w5Lkg0kiEwj6VTXCDKsX9rMpnvIj9pcDecXAIXMnqn2dTUbN6w0XQ9ue6FV/nnXCH7S3lPWGltVcLsH75ub3ab7A8M28caNrIeOr3o5Q0yFsYL80xaa0EY/UEczV7icUMY5pnelAkmUAXmHYjvFWFGxuqlSaow3OM+/iYY7/l/hVELF4EjRqNR/bvRbOY+DUGzGR/Oh3EqmE/ugIQQguGt/eMYz/+L0cimjeZfQDI3phXMbMQsqH+CjwVz/hf4idHovgVmB8gLvjbicDcC/NypP536E/9N/puMibExdohBmNwyiaZdJGoigos7GpF222xrfnZhML/7Z+ylaqP63Hr+m7bdUkQ6/2cXqdfmvwixY+s2ksXFeXcE+iX0Z+Iow76DBNgjJ7TOdUK18iPsPflfQD+DPsZG2Aj9VmKMMJ4fYRrhIaxhTDR0Elh2vA6h/AE6xUb29mj3sjmL72petXjejPy+oel60M99tFduCI59N3221xe7apOvxs6aHs7vab1IqY2tv7q2xsHeHGml/cV06u/8S/xTjJ+JYc0bWEX0ukW6YmIbGkJRMdjJ9mYIH5QIdJF4hvRGyK7cC7ctImQRcUET99fGXOoft35GYLMQu+g2smnkgZUrH8AL/9Si217IssJ916nv14ZrJrvdxLkQvrvtBcjgPC0NXOicO8Qf4mcxPqh3hgUw3DDfdvLJXngg7N3dN2zbPJSaed3OfZnMU7dvmznp3C3bruO+Nmue0LFsy7S+6265+fCKFYdvvuW6vmlblnUI8xCXp37CrOZv4B9gauDBlYp7adcUXB5DNCwYImlXOJJKkAdvExXxVvKEYnCo+3eIskP9qrrfIYs71CccBjfXRC52udTHHdaP1A1ui/VvH1otbrLrpNXBsGX5B89QghDyimlvNB2KfkxZ5C9/em3+d1+d//IfFp2+2Oxn/s+9n/79p39S3s8idN6g0yZObwJOgKUpNB3GyU0Ls0PbRzIRq4lcarLKOJBkLRzJQD4j2090XrbA7DW8K3jNF5hlGS5e4V2D17zgss4T20egOJte5iD0bReM9yjTxnQxCRj3c5kFzGJmGbNKmwGw39IJDJcXJZGMkaAB4jyJAKw0jt5IAuIE+A+U3cVAZZrq9zhDyBrU8oosuxcGNTzCKJfla7JjNVmuSb/+tuzN2H+X4vlB+PpdfMXXmuVsNiub1T34SFbjYw5itEvVi0K0Nt9pNJUMI7SLGRhf2xipfCYf8z5OdlGKayOucFeVPeS/dbo3lBrbSMmwUiQN5/ed7g0Ds1s17IuZC5kNzM3MZ6EWCa0DtekdJfAxz+R/OX28sND7yRMTBcf++s8mQCQWHya4qBv/ufeMoWyslPA9DtMxUknxkH/yfTnm2CMYzs+Cq3r7PxY/MXomrvTEsRpfEGHa+WN8E1AHjElb7d06ddA7oK/+5Mdsv9EtPms0jv0Z5kf1FqPxWdFtfFr0kHfgDX0Y+5PRSG7RUj0tQr7rmfX8DH4G5W28kKeJLtmQsQkuwMP1pk16EV4sl7vrMJATfyUWo/GwEco4rh4XFQgaiUX9qxZHrMQqKnz/c2d8b9TysYrAuXpP/Rf/Gr8b1qwwc5a+euLa6S6sneNXToG2XrEJi4R5SGs8Sq2S3d97bsfCRaTdaLwKClRHt37mkudvXbjwVrLhuYeGhh56bvfQkHpk2CwvwClqgWwuBfndC3c8dwmstj81KkagcUgbfPY8Zje0W/82VPWJHmSq6pP8hPWpotc/EexDOK3qU+wngPhOCiO9MJRm8TJefjelrzoKnG2Bn+1NCUmPE4gHFmBN9jrTigRIpsACrc9Gstg58ULkp9467+Gf/eFnD5/31lNrt2967dhrm7bzI+VT5m+fzKhvf2MzpICEm79Bopkn07lt1762adNr127LwVqQLdJ5+lpQDcvHPQtVY5knhYrK6q8/JsiP6EuhGZdFdaNszjvpqvc+PI0CdjN0AXsFOC3ZfALDJwr4q2Xq+GF+GNbsxUg5NLLIEXi8otcDQcUts0D8eQ1iVDRAMBTsYiNdRIxE09EIBJO9A2xqgERTaW86BUFn0OD2xFO97FAgFhF6OoQ7prYt4XwSeUgQHiJyDbeke9IdQntciLQ1FlJMaYcUNvZBg+FB1ubjlnRNvl3o6IEU2w7fdNPhm/hh+FLysUu6++DLHkOkrSHYEjH0tEPe7WdD3uyDgvAgK/m4szFFR7ch0toUgBTdWHr7EpaWru6+6dmbbnqWEbV2EtxAsXiZAPTtGPSbHsotI2leoM8TePEqgSQprs7AGFf8kuOkPdZPXGb55POAW1d/jLST9v5YflasP6v/CO7+GNAPC2BMZWmsOjp2NNbfHwMCJD+LPVL+D/OYlWEEI/9jpPddOFkB5d1GSuKZYggmCCd7JUxD7EXAzxyirYnNDLdDZoFdx14kivkvGc3579Jm36reTTvDgBnaO6vzyQ6chQmlsMoIkIQ2+bBDWBud1Va4pcCn8CPqxlh/fgtG8IPaPH8C5wk6/nZDv69jurV5QhtwE0x2iqOsj9Mx8B9/0EaUdiPfOYYDCi/q9jhWRuupMDEU0+CtX0sDFxv07T/K5niBPqN9+tQjgEc31NGCXFeMcCEuQBIc/BK4CO78u7EPYvl3yaEfK3vcb6qP1R2tI7vUjVDDUdKubsSrNjYKY1qBEa2P50SJoaXiksIoLiCwnxS6EBuBde87botNfdEWwYvF/R0/u5yCqhGeEOR2ynSeyXjt6ka7neyye8kryBSWE52y+RBgogrXPZ8E1yIHoHIFUM+AbJhE7lbMtt8ApL+xmZW7PwbjAO0fAVoXQOuiSP/ksIVdFZ0aulsamKUzwPZ/NYDMJRBPCxsBqLzqHyneXF6Ej9HlIFo7+pg+jUb3unRmGpstGkm6etOuDBGA5wCMefp1gTHcdZlvPBXlOslvYTp1cd8UjYLVd/J5awNrIOKLnIt9MD9qdrKrWCvA6ALm3QV9VrsPm60Q7+RHJHP+2hqfugo/MvI2H/mqr4b9tFnKSRY1Y5Ek80Nm/WIhr1ikKnxGz9TWXrokf9xwujfvcOTtNTWnxd0F37Y2W79tteBqZ4G5qLCuomw+nSr28QESCRVLTyYKILGJOPfcnaIFOsewhRdvv+rWa/Wih0vlbX6Zb75T5C0qNKVFvH1QL/vazSWgC2s6oWXXIuUxQelKiJbowuJDQViatLmLijg9CQBMg8WiPgiw3LEeYRmm5f+XdnvkDnxLLjMLxtvX74C3OlwPQqx4xwIdpPx38LrlDphiyWUWHWKAzzxurS/xTo+P5wGFak62ap1PVFFN4v/y+xuR39WnIO7lsWfwgVsK17wxrs9K8ltIKuhkw7f/6dhK6gQokFKhWX3urrjk/rnI0pgfpGMeuQIUaEM7+GF5q2iMkCaMQwxxOzcvU0eXbsnS9XknXvP7Gtw5dwPXlFu2ecvSHEZgNDsU6x/GdXBYXyOQjzZReSedeEPY6nEv9gJR4oBQJtFO6Kd0fwC6BO4LNHDeBujB6dSNcUQC9zIv2LnAzGk99bUDrdFY+9yGFQtEo0GQPNv6vS2drj4+1jHbv3aJSMUWP+QTZrmbNTjU8wyG/iXNNpskybLcJ3CiTF5Ir+JYzmJwE0mSVhlxbtbmvweB3ulB6Til5UuUZydpgiFVeobhU0WaBqpJ198d+/XeNRTZ9/1OPfG7+2hwzd5W3D+hmyjsRcUg/+Cavb++Vh2ls3L7zT/etOnHNxeerv313vzLVqPai4nJv+K1FC6040/4udw7sAb3laSg0XCkAAs0npBO6VJabS4Elk/U+D4gTXW+j0wnrMlqNamq4tMIYB87tE10i0FR3LZNhJsb7/R561btmes8YBCRkhYNByRtKd55mqTas9FYhJnbRGHuOh3M4QTdgQSqmgRxuzGdSvZGcbMxNQGk5C3ebLjoXIOFM4l+WKHmLTJwRv9E8GWJ6dYvf/FmEyEGr+gyrr1p5zrgkz0Cw2j94Hv8Jdx7dIVegBSNtgsqGsRQEYiIBoXwD0LNvQ5d7s5Z00QzwNhqZA0b+tMG1tQq5nd84uq8R0zPvX35G8uRaze4jcOHzz0w1+Q2BIRvf6J6Kgatnrbiem+CFvAxfkrndzD9MFPP1GWTUHclpASUkCNAQkpCCcCgDSUDAhDZ+CuEkgn8J7i9nMA7pA4lISappxILKfAeSAbIcSDuN2bJcfZILqeO5rLs0MnngSHYRdrHjmaz7JEsEPw51ZqDJDmUIOZIe34WaQeegNsJn1qz8AIpT3yCjyEih/xELkuJ0lEMYTLVCiWpo5oYMleMH6USyYJcD+uOe+kWKpn1Qns34iyYDjkSLvgnZXcgVQNeqINXr48m3iS7cjm8tedyY0f1QvTnHHdsrKby/+SSbPY8/NH6vpl/Esq3Ae4ZU1HC44KFiI9o7CEgab/RqHbj7s5KAg06s39ZP/zxI/mVuF/TbTSy+3Fb8If9/cv7+wt91yy8RfP1QXtW5RzQn7qIiZyuFM5QfJ5E9uVnqT85TanFx0lkP3ukBAMprvsRyi/C8NAJL1xbIIirSvnSj4O5netb4JxmNANHPssHAcHMHsFRgEug816gDBeMbdfiuRcghqYcm0+Xxx/5IAEtN3fqFF3LzAXqwoT0PN0OVTNqxo8sxMkd5Ig6k79Zk7VxxX6gMLOZFQgvpW2RrMW1D0BDihaXQ9wVRoBxPLfpknmkeMtoB/qM9cRc9IqmMD2XUmdZ7GSRKPUZvChf8BoykriM2MnKYbOHX8R7cLdNCxSFFVQqoYswnlWtlFS2mNkhswVpZiQW1J/UKFfipHGlUkM6UKBhMz1istELIHJLMSctu3ugzfaVSOjKvUgc/THK4Sdg2Wscz69leKIkkrwuuWiOe9yGYKQXRumkC3qbRcMwrvhjNXgdZk3RxAUEhuSPvn3nnd++U/3vlVOmrJzCD8JLxV1OHRjrZifbcFDOuRNTGqdgQm1tSNJ2OcQ04YiEXuxtII1ECSQRoQGYioEsgCfchB4ghAtw7FfJre4WZ9hkVi9MtjuWqtdNDlpMrfEG9fOT6q21okg+e4As38MfGquNt7oUws6Ysarj1/efE+yst86YUVNvDdts3Pv5c8m/aP0C+f8/Qb+IMnGq09BgwN01oIOAnAdagI8mBSrqk1gxTDUBOtk2ousEtBH2z4Ir2d3f6k8PXXVlt2qN9RODxRuoJT/v27wm09jRYVc/e++iyx2tyzJb/n3J0htXP87eSsQaf2Ly0s6Zmxela88REy1cf4273mI3iXNJ7KxrZibOm9xm6rl4fqy/t27smU8tOfdW2ucBzg2UfmOIVyLIl3kpYlwphDISTXJXsctmiDtN7fNV6zelgxwnWxsVr83Aj/S5ki1jL/a0GC6+2L6Um+aoddlNFuj+bJ8mH/iaLh8I0/U51NspIEfq0dohwyFXKgm4NggwQ4rRhCOUFtxxo8XnitT4cnGfT93IS8FaT85XE3H5LMY4zIEPL1hw443wz+1UmhTJyJGxZzw+wsKkKZgUiVtKOKMEb2AKHTv61FNc01PQFwKnvsZ/9pPA4RKTASWahmh+8MxwzHxKy74IRn5LGRjsPUUwTu64UYNY38caqd7HKucZ/tHnODtENw/2UfHRMaq1UUPDJQ0OKkWCeet5fYOhII1VRz8+/Elg5j4Gxur3J8o2PJ4rg+2d08T/fwEzSVbyZ9XPro95T477lRKqUSRXQnauHNsISAl27oWi6Fv9z48JMv8r/aMMj8onCP/DuDZOuN+GPPr/+p7bx+7JlbYdppcNhzKU/1Px5aiaGDn/s1iGMaBcleKUo/v9rcxkZj7DBEKOfrayytXNLYiUdBY+pleQXdnscKlQcpzuWluxsieeyuXIK6SdxozitWyGOV3vOHHjguyCQ6fpIYy2JwvrQEF/Qa9Pdf/QqOSqCiE/EE1/XIVKTc2tzWbHnimrEd+Vyz311Ml3P0GVTj7PD5aDnsvCvH36alEaPMePcMegXs7x8igTu4B9v7G9vTHvhCu/kzIdx+BxC0ay9zRSvoS0F2lIxI+X7klU63I40gLQ3w5ep5na+SFnba3z5D64zv+QtM4n4ffG3tq4aNHGRfxgrXPMim+5487abL7xhdseIRn1KDl+7aINixdv0OD+JSPwKf5+xoP6aiTeQIDVlIhMcL1H5R9PYXvprs3fv2bO7MOplCmweuiq2JRZ1zz+9a/v2PH1Hfz9236w+ZrPXvWfAxlj4NLLHpq3c/PQ3uvmvbrjG7fe+o2y/cLdtE6VUlXi0ASb1VLUBVSUWSU4HdvAraTyS8xzM8NxvxFkXV6pUVRiJwcgC5zEeht4rwcp7ki0k41G0qlQhG1Vzlq8alEmnFi58caB5Q9vn988MLhqyVlHvLEWjtQFeupdiocF/tkkOGPW2ibWaBTkeZ/dvPWazXfOnnvL6jkRXpi85sFzZt+55ZptW3bl1cCCHZPD06MhySha7UFzjcjbp8fOecFCirzAG/yVjBX6OFIaadSjQq1nNhyIe8tVbaaSdHlXIWKacMeuZA1uxS95zILhyrxAdsXTL6m7kNQlx2P9uZf2qhufePFFbpI6/OU0WcP99RrCsrwseVot5mtytpf6Y0gm9sdeyKnPQ7onyK4nXlR/rg7H95M1upzu89DH6pgUcikoiihJ6NJKmRxV1x+MJiOA3YwhDRQrWU0u/0rvq0VYXnyCwsLeTJYBq3dAtJDavuzyoVpzZ99Z0+a0uoiFH/xcqgDR7rUFeOrUn6Cywb8ZeNMbhLV5ugP9l0zv9UN5b5mFkjzxUcpPJCn3V402pRxtJd2GrnLdhtVk9ZSZh9W91fCSH5B7ofxPiWL+j3D/uwhBRdyAyozeZwvQzs79soi+BKSnafLviZCcfrpBpLyimfLfTyJtbyruIQKD01tUwJyKEo/ybaxkSNFUMdMkhQoJyRBQFhnUkDQSXhTM+3NmY0EDM7ffLIjqWEGt8lCO6mLia3PukFnghosJD5p5SIho/VDkzQfLE+IrYoJXkD19pdP7OwG/voIUtagiWiZ4PAFTHHlTVhRZ7dYmPar+NJ+8JhmR6DFK5DV1foHoLNO/pHrvZfmWZ15RQlwvoVDKhCWNK3CCch9lfFBuAqUgpFSShmNaPj+i5++WZfKeViJfW5HnUakVL4UCNVkA4+ETfIqx4B5xSaP2L1yn0zn2ltPn4+OqZGmwwEVCaCSqG53ldtL1oLGAhdMLd09MpCCF6tD6ZnAZBY9hDaYsP0jzZ0j5ZjKsF4i1UmLuhbJMCnYJPt5VwFNvmZawXjEvLJqIH8STonZjq7BZ8gKgR20C9MDFqJAX1H64QW2NEup6qgzLP8cvppL/NNTOBTCJABOHeWoXzLhw4Wuy7gaBtjKr9kgKq8ZlRYBS32Lpxc8vIhpNDTfyNXWybMJbn2RyQ5EmWc2QF9wmSZ0KYCE+cPuYO6b15Uotj2Kd4MItLS7gtFbkTdrFND6pvEZqv5Yv7jXAus7Pg7avo7KDot50NX3CPkP+Kps8J9/3mGQIteY/LGPC+L7872SPR2br5fy8MtKBMHedGuM28/MZmPJMrGgi3Gb1S+Si1/L/zrZwO9XH1ce/z7ZQ1WSoY/+pMb5FT4ua0Wm+Jf/298nFmChEQ+Ti71est4mq9VYI6RsymoRJKYidElT2FGnDTZvqtfhGAFTbeqEw68GqtfmbVa/1IFO1/jdWr/8BDRRtQh9XNjubEm4aWVpVonpTGR7PVGc+KJNoBIWF7kYi4gUV3r1U6723i6TxUl3n3/tM27aZfKb7THiHW9VzFSwHJ05VfK6Ar7kaB0XgPPE0BSkSFKsBUpaLihEWoA9wBt8qirh2VSOkZwXEwyrxZ5jyt2rJmSo9gX7cg6jsEUGJU9z9xJPOEM3uQQxKgkh35DNATnVyrmJ3mbCNyIB/yox4wH1bg2DwN7q9kov4pFqny8oSm3RQbGgJ1QQTs6ZMLilOVYJ9v6Wha3HcJ9jddsXp9YhGUXLXt/qMDnvLpPNTXfNa60z5/yjXQOMq+lNmwh5egpYrdfZQZV9rI47xlRkuyTjpzsmCBSWNkAXVoK8sgYWqQJWbo1RLo6QH0YW6pxqfCnRgkd+RiFjUQUQ7poIaYoakgXxwFd9BuuI38H1xBxXSFb/pBDIKQFn7YB3dB36l7sG1FLaKiBdp1KxLvfswap/30lnVESgNnvjbUoT6w9N+Xoio0qcYOIM+heg940YimsucQVvli9NEcft2UZwGQwLuilj1fFr1i3NP94X+PE7Hpvtj6lBJfJ4R6NvWiaL6MgzWHxiN66DExa+dAdAbMYX6HVF8A+7rjEZIXAVbDe7PVI9rmN69JOLV1DOSvRPxWNPZBZf/Nf+Ny65BhYxxxV+77XJ2wfQ389/IQPgajXbwMsuAz/0IaQcXJavKbRqR2IqyZruXjVC2+hdee/5vdnYOedpmVtR3NGXldxSzDSIiBVpkGb9by89UpEPKrSLZmyFDzMab/wXl2CNe7s/qCtTvWgG5kpBmCBlSzDS/r8N4uwBwohRW63JTS1y32f0TQsPfXVGEHQrV8/NCfiOUVirYcBbIeA2+iF68rQIo3B/S628vYESr79ehzS7Q9LEL9UXmik9XVHb1yBO3Ngvt5935+k1efkV51mzzrM0LL3/20avnwMeKuWyOUZg2TasSqZ+KcZQiOn1Iu2Vh497ALUVZiCKt/gh6IvTIj1ZLRjWAkpHKOKovNwp00eqPROiAbiNEKieXwMLcXhVJ1/uzmLP4tfxaHR59cBdJVG1kTAgl9ze9QKUEQ946Hkb+okJ5JRDyf54Axur1D+WS49cLr0tTPEu7UmXrxcSr3XNvumv4yXzInXKH4F7Tc7p17Zt+t/qW2+93k063X7VW6lALxTY7i1nBXMxcxmzQbabxz+tJo+wijYaIGMNS8AoSMgAPt84DdHOoMPfjXhF+kuH1tZvuFQrRCN07xGcXRX9MYxYchDe5BcHj+Z4i+42WyPc8Xofi7bbZJN5nJLJ5qr6IqRtzqNlM17SpFsnkEyTWoABEjz4JXOQvzWYuwdnV5LNGOwTM5v9r4RpQ8ZXsYodks3o31JBlzbYtNotisnm22MxiwGFXam5oN1n0TA/hRvshvTSDwHff4nNzRo9Dum6PaJbMXzDz+x+Fkj4L4bFNBb1asqsgH7Dyh4DvbkPtf5yMDKzEwyoaESMSNS9P9gJVA3/RTlwoMwZvxECFWxIPNw9gi01nOHjP32esZTtmXHnxvZd8ZtakqQ7ekajbXetpNa6ocTVxJtY+uSe69OLz77zh5bDR3xjZMzUz6fxrz1nqrZGcHQHfPVefN+fiK86LeXj+Sc5lPKy+k/vCUI/DaLFYCWHr6nbXuILTIsb5imNKY/rCm28fSMxPhkN1XbNMNZGuqwOBhtTSxWuTk6bw0ZaG86b1hKddePOKuBvmiguYBn4T/yOqOyGRBt7bKUI1GjioBC8aUKwF7Q319UgcmtFGIzCJGBqwQij0ynDsfdFGc3TS3BlNfJ25xmzniMkpXXTPvCaD3ZaZvyzjmZdudBostmhb0ORZNN2sJBeed1HXkrUsywueQH+L0eCPxmsa5ZpgRJSDZ11yDv+jmbd86vxZfc1WcZJ3UkMq1BOOOVtvu/+pB+en186d3GTwWAw2jheaJs09/+LNfZft37DALyrNj1wABMuUKbODyTVnT/KYbJ3Tpq8IrNh92dkxOj5P/YpZx4/ycyiVcDYdn4JbEoKdQi9054iBKsygLW46FRGxAb0NPNCm8BSNCPjoKcj6EAus4SuP3rB+cV99/eTF6294dA8+TK6v74MHVpYNRt/I30e8QGTOOdfGWzzxcy+87a7bLjw37rHw1nPzp0KyyRSeZO+QQhInt3dYgvycjrPOv+T8s1rptaP84VeywdWX2T4ysr0/7TLIs6+x9zib56ye1dM9e/XsZmePY3NDs9zlnNVt4+WgHJbbz3Livg4P9WWgviOMm4kCRT6I8vw0NbUUEnFvOuFKoxQW1gTsvFirsF5pb7qTUCx4i7VmtToveaDxvK9uOaedVvPRpVOnNz0Q6bry7uiSdQ8t7Vy4JQKVS+XPplV2ts4bvCwZu+KzgITtxepaPRzWdpv74muvv6RO0SorX6cu/dqKn/XWnrtp/Zragz13DUCl5myiFW2Ycvb0PtsXnU+tx8pvLFbUspLX68mdegwmOif/NPDONajTGoUh6tU56HBJCTBASVvNUB5VIiKpc9kd7kludodSFz7xQbiOmMk5dOYk56gzL6uaf7N8a6MQOHm0ae6snZpFDfuT3/jdYzjzwkXXIVHoXNuCfQslQZqBZjTsoHMqrkE4jaYdgkGz2ATOgB3cPkSukD01DnV3ttb1wx+6arPqbkcNAHoFPzKUUQ+qL0k97pjbZv1I/egC9zTFbrrlFpNdmea+gIgfWW3wqkcis8ky5FAcRd1If5nNZrl2FFpungc8wpoCl1BpQV/ScS+zjlASyUTVv/AJ46gkJI4bHX4lTnloctxPZE1ckS3+jG2fKIjkQFyzuo8jvYQG1OrGvJPSTu/nSp9PHNTl4z5hK/8gtXVKF6gEKiglgcKiRlCESsQCV5QIlKWKpr34lt/wkSx/JCmP5/cBKQfl/5gd+rOS/+p91/+YCg5CXK2W4M9fu+/6xxX+vnelVuldIDCG0VQTpU9Dw4pRfei+6zWx0MLie0gPbyrkmRU7OwT16JGeyXLHqOLqAfVN1GPlBzWtFNzj0TRTCjogtP1NjIvu5habN5Aoa1k66wGpqriVetJgiGdwDZtKhnN0y4n9sXYnsqGmZfDSR15+5NLBlhoDaedEm7sxmpqRija6ZEEg2EAnTiAC8IrmFbGz1q08P9PSkjl/5bqzYqT9hMmptEXDgTqP3Wiye+sD4Wir4jCeoHbbp5hRfpB7BakUIppIlPCD30dR1GtslDz8OsqbXmejFC/v8wu5X2myq7SJ8Avzv9DFUJySf5uNvq4+Ti7W9D/OZrLChdwxmPNiBRqVjnpK/aGxRCDspVYKAW9AN1JANoo8wP4BJUlGqdgw6m1qPQ2QW3+OfU5/ieLS/NuKpDU3uf8bcAXyBal5jMR2NEAbPAZt0K3hvxHBEDlUxfIGcD+N2gNSNx36nfqlAYow0puatNpRz0e4W2oahKzQHsjf2c16ad/3t2KTtPobnX6D8C8pd0MDP+Kx7wnXqGGlLQcvikMErm6TmfsuxJXbSAxqNjOogJLQBLiKEHAE+JGTS3JoEhTrz8/CB+5YlupJ58aOat8Kv4JvregxwcU5Cp8GFAFm1FyOfto6GS2m1NGTS6CPNKkbsTdCBlnN9onMho55BX8IJZtEQ35lk+htwN5A0V3RCPoD/yXAcv6pAtbZczRUA64JmcUf4q7Q89ZHLeJVZ5D1Ps/t+0iCT3AHVtZC7JDCXfR7OSb/Xja5H3zQbZL1B+ULX1BMTEk3AseSpmnKEK4T9ekMIidUCRQFfcbj7z8gNLvzF7mbhQN8h6ZbRset+nQWdS/ZX3k7WpS8P9sfo0iGS64wV516pOhjI6TZ2dApgI5+LhxywYoWxKUrykKJsIoDsR4mSrCTg0egMPnLW/3Q5Nn8BZEuzqEI7HK3n0+zFmuO3TtWQ5WJoG9YqCD6Gc32SxnbnVPfsxvrFXK2dILl7bLthDp6glhcsfp4bYvbSmj/mQ94uBTw0E73x2jbNRCvC6VL6GCFDwU7eWQDcC5FY5s0slieRDwtAbRsbLXbaXAuu14e2OJw1dc6jQ3ZdY8v7rv2/BWZLqvFWVvvcmwZkK9f5jS4muO9yR5res4kfkRxhV03L1RfPOiPtYi8pd7jNEsOpyTwxpaY/yCZu/Amd5Or9uS3DYaeqVOhH7gZN/8I/wi1fEuLXvyNivibjuKvN+1Nc01HF/3h+ef/sOhox8MPd5SFucPjorQwXT+ytA8EmA5mamHNFDVhBI5pjZbQpugBNkO8MvRub8KVDKST1Wag7D3xlin1ZF7LFP/79nbvCXFOY+PUjrT7/otsPXXZ4exdPzuhZuL5LUXVAn7k7PbhG89uz3b41X01gbjP1xwlu5rrvvf9+pbs6E/Vu7Nk642/PYRaAiUBdrmO6CDTBLPQFA1ur0uXoBR1INDMkypKpoTqnSMx5GiEdTEaSHLs0Alvu/19/5QW9Rv1U1ridT22i+53pzumbs+XFFXYC++CGsTj5JUT/GCgRt3n78i2n71FHG4/u6X++9+raya7os3ZbDmgWfXun44e+u2NZKuGZ0HiF8M4TlMPR+EU6rPKRJ8wOU2RFUFLex3egEsz3YqEAq0cqhAAW19dBZIlVzR61tuIdTnpXH7l+uXrbjPUyep+8cl6aXKWhPHpDcXl9KiTWDNr4mBQc8Tq+NzK/OKSbsfl79o9G20R+brBXYvUg0rLHhtrc4TN81TTOWSZ0gL1ZVlOYH2ery/7XVUjFMbzYpg7UswcqJPQwBd0LKLabJ8IaCr2otcjSkIrGwootKECaUd4XH1+SdazRrfddkBU98t1htvWrbjqSqjaCguxrffM/5zDCpBALUycmajhd+R6ww4SWafuZ5eU+tPid4lgd3gt+b/Y9rQoZNmiXYPXyRHbRs8zX/f4WIFjWZJtUdSD55AP3xtXH+ZipC0EqdBGDA4CoYEU6gRLGPU11QhkLTBiEYPiqOeQgwTCl9aok1Qr5pFf71qEeNxjy/8F0GoqYPv75Yh9j3x4DuJ+uEzHRpAq2lMqb+qfTdiq6kGtzfOWsv0c7lSeMXDHBDe1MT+LUgx0Pg/p87u2UicdIvqQi8DkxhcUwUXCedMpb4NQjwY3npTmgsURJavLwCRyEcN2HfWsDVGfv/u9ZUWUx+PYFueUKwaNvbtu+Xps3eVWbN1GcgVrdMnWJ7WmJz9SD66EBidag0NF1Ukep0t5A7sFCWdhzvYwHv6L/BehXuHqfaBwBEU7hfVLcXvS4VQv+T/vaSIl7cbeMc7ekv9i8S3e1L5xxpvMGcu1EYPbKyCiijjGXcDKckm43PqU2qNWlXusZMiqF82cuVzolUHN9NNR0HZPxFPV9V0wLtvq+k4DqOwVWDlzuQLVdqFiP08cRX7aRlBVfR8cb55bWe5LExnlcsDp1vAP8Q9BucPMk1Ulh4GnN0SAdxcNHv3q9ohx1Ati4S/tkWjIDe3hQdkUGrGRaFBiUdiTSkI41UkMuuQHP+EaSQYlPQTFWJF03BNPpTu5KFAdkWgDukzsZKMG0Q1TAQQglScOaP/dsZ8+fP75D/9Uu5Gs3FY/2SxPld0DHOciXI9gqjcEidXjE+3BLosy0OcX3T7O5g65ROGyzQ2BZs7WbZVnO5ydLe32hMwTQ4wnnKXW6XW5LAa7oaXOIHoUl0FgLQLH2by8wSTWeAx2Y5PDazK3BqZbeJZwXGPaYhX87ZNszoDdaRxotXO1nNlpdvAPFWHDm8PqEE0sZxDEqGzxisFNnuCWetPcGrObN0p23tTZwMuRVodSV8+LTrOV3eRvzjQZiSjaLYS1WEJe0kNsJlZu9LFun7++wW4gRDRbaxw2nrOGm+xOj9cmtbp9ZqeTM1m8UXfQQCSTVSQox6pvtjot/FpHvIUjJovFEoYvHYV9C5Y/xN9OfcalvII37UEhTbTg/AQIaPb4Vz6j5u8/aViycMod/fkDcpu8QZbZoeBi/vbzP3XPsZvOubMtaPHkD9jt6+U2O7vqU/9C9SMvgrXpQNG/E0oJxun+CiElUa0IKQSUwERxOntKSV7ekcuh9VBZBBo3VUcB58ofKBHCwLyf9qFosz9Ibf8dGqwaBMjRig4SGOZ2UkWI7UiO9OfUPdxOYFApUZyfpY7mgEc5rtNGGk2H1lPhAk1Hp/VAMqQEHEUfEYkkUQq1JMdzsX7kklRrTrUi1wMcDjmu1YYfATj7Y+pGpPEBXuoQIj8rR9mgCl4C9yqmF7xnVWxGVniNqtpVmXBvQ6iwni5YQ8a1jYrXtc2J13HvgkvqWxuva1sbr+P2S5ceKGyBwDv2DbrToe1u6BkAJV7xnVLUaq0sJB8pFqcUIPi3yuwxi4JuLr+P30f3OkPQ72aO0xYo3/EsmO3QO5qEF8S0qQH0UsKXv0brnl9+8M7jF174+DsfvPOl1au/RL5/9DsbNnwHL2pHR1NTRxMZhJtHktOOxLxErPF6YlLvpC9YP73x+4ofw+3xVdrHcDE0dQQCmCRgvt9b35xINDf1CDcRSfJ+pYl+Sf8YcurfmXP5F/kj6J82jNsrkWiEuhVlgFfyNkB3S5MUzLhoNiwSCYcxQ7Ui4J0Xh7fmqRbaPa1tzujxkBRlsEHy0/OM4pYLPb7g9O6BQJN6l9zQ0OGyCaZz0vMTbHOzXfQ7a2tsterTcqxeInODoemdktw+1SbVhKwtW9ffe8VKadK0OVuC3bWzyKm5LeddsWTeorWyY9IMtUFutdu5g+Rn533qkocdvLs2HmhU75br/MmWtD8zA3OP2t1ea636jEzqYxJZGAwFiDEd61oTsrRuW3/3pYNi3bS+Rd+GjOfVpAPNd6y64Gsz1GaZleWIPoYL/v9mTeQBENVEguiF1aC4YeXxFETw6QyPfn0m9g8IrMFAvKM1EI11DARnbqibHk/Iojy5rSdgCyZi06y8sS024PeuO4MfwQ5Y9yKRZCqyYaF30vzeHlmUprR21tR0t0yz8KZY66zWuGvxVQB/36kP+K38t2Hu6NQ9SFJfw0AdpqPEK2qTMpf2VCqJwqPoJezTL824b8akoL+x03nhh+oNo5e77psxg9Q5LzebIKD+fsY34f2MtB9fk9v5b8PT6tYrgv4kRPwd0q9z3gdJSJ0653KjCYPwCaR5aUY63eW48O/kdo33yxX9wCiMv2QTrk8eGSI6Ag6moG9t2P/F7GRNlDjl0gw7pJ5aOXXqyqn8SENnXBmbSwUYLyqJjv3UmY1nKr4t80no0faXsaIEiF/BRaIBnItSce4OUif7W6Vm9T9H1X9Vj71BEm+RdmIJQST/ZfVdudUvh9S/qqNvqT98g9SQ3lHibZY0mRVHooyDN/FHmTgzjdozKw28NwQ0hwN6BCoPKaEk3YtKwNhwRLXuk076CGoZNXDQcRwZvreTZY9EZi+d0s4+ztv8iei04JQl6ZbDD2eHV7X4uHuFVfPrOmcs6m6Kr7hssr+1VZFcEZ/PdJkn1hOs8SXS/NFFgqt94PIZzZ3tdaL6Q5vo6piSzdy737pwsX1VyxUrF15iJ4uNkq+rbyg1Z+O8VsNC1UmcvORPRfxtPrfRwL2p/oA1eZp6Z/aGffoewaXcA/xBlKlQLfhQL/oPgBGP3qsA7IQS8qDVNswHKRSheDUvA3Q7MZoRcJMxlEygujn1QdyzfPfq3dEp/bXh5e5YXW2Ngfvza0ZF6UgFL/E0fTq4LBlvTE2qb/KuuzYSXVnjTfM1osvqMHVbm9950quIZlbqaL6YP7jk3kUtA0GnX2nvq53f3WoSsvEdDRnULgo2fN7lNZJgI8/VWi33c3bBZnGY05+dm+3qc7fNmj4YGKLj2nfqFP+g7jdDlxEV5XsJQZP6hYrS1l0VQr4c69Xueixp90gnZPmE5OF22j+SYEWHlZ0K/Hgsh/Ztsbh6h2DNRlvv6jJh9XaJaHCZDiUDKNTMkvb8vsqCyf3ZNdSmO0fa0Y4baJTtpbKzuVzeeSI7fCKr2Z0WypapnXJ4gnoWy3PoUIlIQ1TXdqhQJIXp9Wx5fYdpeWh2TY5D+YVyKd0jw3iumwi/BC3cEy4o83QlZnW79MrCgCjbhWXBlRZVVZZv4rIKpXC01HFlHdHLoeWVl6UVc/J5uGm6CViW5mulYMk+HqNYr0AyUPivLg2oMs2MPqtuhHyRyiwvNJej1Br+fcLyoAyu8D9B7bgmzUqfFobF5nKnK4+t8MPJkI/xHUNWk117jugWF+xazTAALQn6+UE9lhoI5ApGA/iuJOsrlNP28SVVuBVajXmircLel46w2bJS1Q0Ft0KDuikDFL/3pYrid1Q4FvofwRIo4R9h2ftSwc6jHAMqLcCql8YPHtlzGoByNXYN6v8hXnRaOhUvx0sVLCexwupGDR4NOYC7PePa5keIPACnuAdD7dEadRuTIiS6Lb7uskb381My5yjzF8lGCjBRqdwrWJCagfB3yCy7XT1i92hbcZ5Ci1FJkgYMDf6n+jspIsHFjJrTOdzSMuOa9DbDcj/nH9N9bIoGVgzHPWIQuFuYtaMRaq8eCKI0gEF6lPOZjBz3EEvaaxwSUT9U/8JbJZPJJLBLolH1La/RbF9AbC8JJjv/mMnssKjLRBJyqj9QXxNko0Ux/X79epfiXkm6fmKwF/en1HLc6LxloXWKvGa5rVCVL83VuiPcDEX/K5pTXOxHfx6HHB0t2FI0qI2rCZFTrvPWU67zVuS/kTsLnc7IKhFg30e4FOkqNSfH5PtkmUy6Cpiv/36k2sbqCeCFNa+URpoY0sZoYmCgCr3qgZz6s8I0gP1bYiR+D79H56NOz0EVWCTy2/fffvSCCx59W7uRV9995eqrX8GLesOXNm360iZ+T/El3uZqL+FyzSZ8XxpTiI/G0nkT4zznFZ0t4ipMz5v4q9ssqbdKUZt6u82knPCrt6PZwsnn0XySVnyPR1ZXAn72yx48bWJsu7apnI3Hy8bygUK5Js32qcytapqgmn95uexccj205vGgJ+euOeG2SORmKZr/qKzcx9SFctMJdwMUFZDJITs7dnOp1EKZCxg304Cevyfya+vlKqv6aXK1qIj3imL+L6hL+yvUlFfE0VKZ7E8gBY3M/8VoJCFgizH1W6VyC76nH6b7jiibYVxUmVIEspry/LgZIlCeP11Z4zs/AwvVwtGFEut5S1JY4lfyT0N/evOLo+rUEgjcqc9IkGpQbv3iW7Co5b+KgjvpzYdH85PLcc4X21ouwEGl/S4qnUAvoSlXUUhR1eKr2VWFTB+GMl6FsiQsVD1R3urlAAIoSn7JQkmiVVCHSpCwDH/qPepXQ0Db77CJOAImohB+RPWr31ev5g/kE+zTa4lbvZo8xdWPffQu9yJTPCNB66s+zXoJt/0L6hSoCuBIoK8fnBGG87OoRckJpLqyWe4YbpGi50g0+3I3UD85Oa0fzubfoXxPLbW3FDWzigmyJeM0tQkax7PqTy80+UxfUHPlBZIRVNQ+v0xRm8REKPoLmNr0+Uo48v9GFbXPKylqQ2IKm00QddgyWGMROCTxdLB9nCY8P7j2DjlsV/+mfr0C0r/NkeXbbpPlOTBBwT0mVz1zx9S/wJecBF9Wgv3p032iP2v4VSgfgW2G+HUEdEXU6iq4CtpLJfIN9XQG8dwa1VoO8XC2SrPDDyCOQptXgbcPvlAgBfxBoGwftQKeKFrNTASPt3pGGqDt/QRasn2kri+H6L80MJRsmVYJrAKyDItpJUy3/15WYIJqcJ9Q5N/LFJ4c3dc1URpWl9hW6mu50MUIelg4ucTPf15zs5DFo1c0VSp1tKB9jkwIyuM45kb+IP8gHed+6jO3v0KbIknzLy636E8KPTdCuUpB0wLo9JKnAO6pv0vS31EtBha/fJemkgLVVnd8KCk4qBTpQ5m7FbifBKrPJcq0pZAFVG/XbOFz+Tcq2MLrcmV28Nmi/OHskh82bau0k8eWCaPijQPWQ5lUvslwVCfHkXBMIehqUgtDNLeauH1huvZTbYmw+luPjyWoNGEuxRLR7LK5fSyXFUyK7PURQv2v8D3XOt2NJ6liBbmPGOsakw1kbeOs+31Wm5qpH+iJWSzqdPr2O7zc2TmtnrzCig6bBd/vgQmzOlz0STWIlmZEQfupogOZFHUZ7EkUnMn0RrpIMqAgHRJAOjIJ3yGw1I/MAp9q9S3Q/clADNm1wEeO+xbwg5OIYHZLY3ehG5lJk2xhco+6JWybpEVz2wrR6hZyD0QXZbeDVB+onmlimpkWprdAs4WEZDSQppsDlcdCBJJESIYFuAtUnC4GIF2C3Uu2Kv7L1bdz6FxtqxpG4TqQOqOUNAJ2HLvPWA2GgDy4O4vaDrtyl6P+1fAll+SyFcQ28GHqh7fvvf37udylf0fNwhzgz87Y+cf5x9GnF6ygHu18sAbipWeF0YPBgp2GaKeQduxxdEr3SgbH1kvH7tvqSLhedomOvZyts2dw8acu3dY/f+ucuMtCuP/e4zC4XnH3OLZ8ZuxTWxy8dJfU5dhDeKPSlJy5pn/+7u3XrJhmr9C5CuleGflGQocKnlAUaRKp0BAHV0ZwUt9VCqk6zYOgRIuMfePJzdmBdpPJ7/6B23+f+sp9NMDZevovvfYHG5dGPISQq1DojqNckchVrCcCYz/Q0hI0m3NKDRfkgsrnamo+p0CAq1FyvC3a3Nak/s5VX282x9Ufy3E39VAx6o7LpCvO2wK+ch9jNqpJCutcIOooKnYWtDK8gTRVYygRQfwgzKM5+jP2jOZdx3r32Py7rQUPOzAnoRs95NvRAR0qLGU11Taqu1bUYSzMcWjMEir067JQQHfIrLBHsrgv00/Wavd8HRLMEEYFSW3HCSNQehnrHztKqHcDyo4VfZ6gPKCR+gufwA8GegxUEo4A+gd0BASHiH6jYMLIsUdQJTs/C641KN4oCHWolCMLlMfIdtWKScjx7SM5LD9HnfmhrGI0S139UWfUnxgOXdJFW+AMcGjKr6eHAttHF5sUoeArYKDcxMSYcKA/xUDhPiEOEAPafSIUFArN0r24ynI91EPARDXvIDYyvqZaWeroBOUABQA/E+DXC7PWafDLQY2oiwpUEyj4RQtVlUp1GrM7In2p2A7VuiOW6otMiGOo5Mrp05ejVuTy6dNX/k/7mybZQ0nUmfrbx3U4KueDnlHm5wdh8FFeKnoaKKh/TK18StOPhwG9Xo5mqXAxvw/79YQwwDR+nAKQQ4izVXioB84qcppWB7IqjU45z4CE17OvF1Dw+oTFqxtz8dxwtogBnF9MjIl/in+K8s3hM9laIn0TiCbTAXL0T798bPXqx36p3chrv0O+GC9Xaj48Ecv8U8UEeBvUEsDlTepiU5OvlpeNGvpnKF0RvUooWhIjnx6GeBapXCQYTw9DNg6/OC3gZjp76oNTj9Kz6Jqobxb9NDqc08vcKReOpcsQV2K8InXFaXW3aI6Ofr1k48rp7CX7rx+v1UKPsfvzQU0Kc83i2VdILmd2/yX55zT9luN2+Cu4nKfwPcK/CvDVU+pHh8+LaldIf1fA5h3ndT6Fln9/W/9Ce1vndfvJtnPVO2xhm3qbafHVCN1X363UXHq9xuVD8OSD29Z8pZ5cZrern9cAdGW/uib/ud+VK0L9a42r6C90kL8KzxwLQw9NkIQJL0ASU8M+VG0KsUdgdvpgP/6NqqP0/gHZFUfGEijZLHpiIgvV5/Bltrj8Qd7XQd5p4P+7tJo30NMO6VGBwahSPMYiaaBYoLY6uEnciyhhh1Z/vvacG/rjpsvnpzs0B1Id6fmX8119l88XnOxe/uGrzzHcdu7UtY3+2vmXN5zUyj3ZcPl8p1sZSs6/nGXtwrV7Ka0XZdz83fwjjINpZWYw85lL8BRK4nGyIir2RiOsEyipuEcIakpGjWgBjLiHWOgj0Yi34gW1kKPxHt2Na5q+lwg1RdRSpFDNzosb44YJXnAfoEOpZW//6u1lhYA6leevezbI26zNHO811M2dc5HFxpk4i1jPC0s21/BWW5DnPQbn2X1WK43/aM2n18DfSoybbNHijFpamzXI31eRibGUOxSu/lT96YZlq1Yt20DaSBuG6knw2eusHs5EPBfNmVvHKdaQzcDfz9ZsXmLDWGXy2U5OsYSsIn8CS12jQIyD12KKqZrLPy7mSPdICmd6WGHG8NDZkkHuE4h9TU8FpmUO/VjC/EinToFyoNDz2p9XD6g78WgQdPG7Z3R0T/Z5dTM9lsL8Ktek7szl2L+gQwGgwkZHc2g5Su7NvVqwGy2Ua4KSXUwt1X4PaM5paaEu6jQ5zVFyNabxvUksVt2T/4VeamYPlLtffdQsk+2sUTY/zDXl/05W53/Bz9UK3p7LjapZ2ZxOm+UlZXrL3HHGqO8+wVroDaCTTnTxitMxmiAAYQzVJQH+nj3oIHnPaN6Zq6sNSLjBl8tKgVr2mj/9CWi9dnKca8rBQBsd5R1tzVlgrl5pbnPw6kZclCr2CHxMnHohLz+3KRQokzALyeIKFU1TNCiayJdoHvDYe7K6mZLm8S3uJ9dojuaJ62/qN/tjQxnSnhnKPw+LNrLi8ZKyJ3x1YhiI1aNAtP6NzCGzYv3DmaGh/LvQZnt0evgIhTFV0kE/PYxAnOHhCQUZdCWY5JWJwMzlAGl1mpNbDU7yyGnhRMILsYhH3VRAijrPcBU8/Cj1Y9NY6cnGVW0CjTLaz7E3epvaT/LtTV72Rs+0WVVmd0dz/MGTI5F0OsIviaqDlbbO5X6xT3PeXbXHRtf/z+fdka+eKPr8KF7IF4vBsT9MFPuPJMBTBMq9hQxXelQ+bewnf18ap4Ib+mSMrtDU5zqlD8QANa5MBGh/OwOvSDfcV2d66mfEWsbGWmIz6nsyZDWQSmqmxDneYyvjHPmRXHZxeueyRGLZzvRioKnGto9nIPkibAJA16adcOZRQr1iAP3bUyBR7T4RgAWTKxhkCYFwshq+7iV9r0whk50cmRcTg4fy5x4OmmNkHndIA2+YuMbmE9dwGYB4KFTsvnDE6Ah47r/fE3AYI+oXADpkdlENcZ8OZEEf8FFGZNxMs6ZLpG3SUFLL7Q2kcFU/A/Jsw+vWDa/7emewLaoeibaF1B9qUNnuqWK3+UfXYVL1v/omD15xxeDkPnXTOKSVcCbDGtOu0YQNpGAP7U1HU58UrqGu8xIbHtkQ3LVhb7Dx46ET3Ffcm1q0YcOizNmf3bC3VjWfAcpSv3MyTlgJ23FHQgmgvk+gk8pL0mcCDOn08MDAQlf+/SlTZ1z12fnqntOhbOTL9/ZdevbAPN+yby1f/uUtC/ixm8ZBo59LTXEW060hGrTDplNprWd58fwB/b/E27BdS/s7U+rGVCeQ46nzaw9QccnmZerGZZs3Yw9aVHt+Kh6HN4ti6lxIhT/wahnZtWwzlY9QHQ2c79C+dxzvVDKy8GqKWQERO9YAKbpsDUTLdWV5dE8PVPjvj9pqw7ah/PFVtkit7aj6G5xY9mfJrCz1j1e0BcnPol4UjtrCdbahIVtd2HaURujnFJR8CuOuUUfhrGhgKKgjCYNSvCc1WKlEp8wHUaAYynFNyzZn+2MnYv36dbMDBTonl/T/ma5IKAyEGz+4eRnVtaX6tss2o34u8mWorFtuFgm4A6qK/yp/gLEBVat5WnPDdKA574ubuFJ/IUfZ/Y2Nt6mN+ZNNTSTaeI56gKwkXerTe9DDHUw8/H35FY3nNN7GGuBKWhrV9ep+0k1WjNWVaHkW1yA+QHWNu8rtBw2a5YXuE40rs7/GA+j09V3hA98yRnFPOGr8ltGlsFdD/7tRce3LH6Trcneuiy7K7J3khKu+3qUaXPWaX7T6/Kfj9BX2eZq2XAcZT79u1ClJzUtHUqfqSMWBcZS43Ena0cUGLgpkKxB1QM+0Fxz10wgg6r5rltnFpH05pepUq3Y2HfYqeKRntmUFNz+XmcOs1H31U6cC6RTVLfCg7RNBF1UF2/wBgu0fFQtPEU1sSg3VcNsR7dWq3af87tUFn1l3ltXpaJxpNvtcZkH2WmMst3JqRpxUH+WC0E1qOGtP66s1MYv+VLu8/XFXvV/ZbunYYBeVN64ls0ur6NzpV9xzlmQwB5qC4Tq70WC0tk8dWJXeHvkD0h9zJOM0vD86/1NJMaIAolctvlByferCsqOKDKceOfUu1PsmoFCamV5mCrMUOCi6V6FJosMF22AcrKJgQDVhfYh6tepp/lYgvnCEAbJQ1L0rOpajEmRcasMiPfxhgGoVo4rwreQpV6fUJHH2e8fa1s2c13Apl1b89a58ozdoap2sjgLN9uISl7P1DrulyeIkt0zr6JjWocoPOZsaXPb6jtqBblsgsaRre2xHi4nELm0MhG1+x1SXwLpFi53b+aHRYo/IrbZtuWAKu5cSEXfybnnmUCaXGTpQr0xK2O2WWY76f+nAjNVf7nCZHU5XqIkTnpt6VtvsFlPXg1031g/VRdpkkyVpD7jnmax88QwDvg/66NnMRdRXTcGTmQc3cuINwN5IQqi0yzb+YFVHuVqI5s4ADfg5oE4ybDLd28mFSFmYvRoomsWXEdLU2Wl3GJy93ZNb/d5gqmNaqJZSO1l6PVRy0nZIj/45EetjLguh1rLqR+SK0hO6NrsqcNX8zoUdjQYDJ7tb4os6+i+Y0qpY2AWlnLRDWdGFTfGY1gV0zNAtJ7pdo24se0D88AwLY/gZmE9iuP4V5v7CSR/RThaHLh+UeBkXwU6BC7lGOevK65udTv+tS/PfW7qj3ljTcj3b9OkbV85t8xsMj7Ddj7DGpthZKwKPvso/c/1K9aLE12fMWLV1y1D9ua8lyJdWXr/bG+noCFutf/mLILe39ITUV4igr3876fpX5g2zeB52sWnIL4fXHlgeUzOx5QfIvJQyrKQE9wHUqVq+PEaOrz0wVvNbJZVSfsuMzxN4l9PkedFzw9V5Dj+nzpgoT4ZxCxJfC5RWLc74YVHxKlExCYt0JAOMatREhHBSCAtSfod6x6Ls8HCWECLwXZ9nd5Dz1T24JUdWs6fU3++fcnT49Qe+kBs+wdsMZgPXMp3U5S958snPP/EE7bvkOPCuTUDTUQ/UzirLhML9yPahoe1D5Fj5jWsaoveyP00PehdUAHk/seDVWsvDWXXXsyn/4wfpXc2V3/Qxli3jl/5hj/83avSCfpTNxOEKLmTjxOEKuxgNlsQn0xgct724mhynupNW1Ph6o3RYS3/+2TJrzLlkFz+ip3qCHKf6eqW02QJLjBYuuj4sobhCWqa/YHGEHpcnumuWSOhxeaL7sOakNR6vvmo+YcfFA8UFXEPZf9UjyudIOyNwx/i90DdsujS/FX2UAwvWSVK4NxaMhAGw3oowp/uc8CTi7D2rBgZWwb/60faR7SPsEbjkXy4G0XaqhXPwe2cePjxjxuHD6ssQuR1fq6PF0E+o2t1nePTn8TUmxz/A3crMoCc7egESuoTHYc7mYdg6etORoOhR7BBGD+qJopELrl4S6cJNRtEAsLP/OdvnJq0Wo0GolY2Et9VFB2Kf+4bZvVyxfOMz3WdFfSIryj6DwWghre7aQbdiDrkTL3A3vNDuDpk93HqXwam+bWmUJZfNn5ozKV5Pmmq8PF/jVY+2Tlk2M2RzSXKjmbQ4RZcQavEYrN/9rlXwtIQqzxQNMzPPfHYLvuPoO9TbT8bpGw5CQPGd+SyX/Cyf0Vxjd2R9NmsunnXYa8xGHzn+sSfM5J0y0DZEXWWxkXjcR75KBLNLHi7XvX2G8VOrf4Ykg0AMdBESIpo7MgAfyakA6rkqpI6UjNs0px7cMV+D5BF49Tez1VGnYmq0WIijp985m4Sn2gJR9b07riPPFo97OYbUZbxJCpot7H/lpZBicglCPN7WOfJkcHqc3ElWqvvz/1E6bIQrG+tz6WkM1SM9FBTR7FSs8KyBBytSmNEoquJNFN5EQyTiCrnKDx1h58yxCepPHU5nxGoxEQeeOZi2m80DxNxncVhr6BmEfUarxejw+WSiHhWk19bSY7aKR5MsteblJpfTLtjimBouXsm3d3djjYM+wEW0El9dM/ueVRWIsXwe43R7SgbVZqrnqoJ1X/kuF7pcgf8duv4q6vayV5U9zMV91GxO59UUjW8rHV6u799WzKMT7umRCXbYUKM+foaCcwgaoqZUtmodV3p+X7akb4dnU9B9La38RPFUG2SCC90tVA4XwEFhyOpZZrUCsgWYHsczLFBBVGNtstoN1bw0Z+O4fYIbvZVt4EUcJEKOhHeincWqONw+q6w5Go+WGOSR7LhKV+KBqbBPpfUvOf9QqkpDyVhBeyyZQGMsdA5FBUqvFMtUyGq9vjnsAJU4UcrxldP1CCaofyDkSAifoP5QwWx+SyUGxp75BzGAvtG7uQ38LehlyEQMeh0TeE6Bm7tYdXqdkt0uOb3kfYlNwmOdDyacOq/qlFo1v+PTmTi3E/glC9W11b34A22zmLzvb231Q0L2Bgg60OTW4YdstO+YOJnO38TtpH7zy9ymokWyA79qlVSn38HtpFlImFnhu3b4boNWXklOXV0Iwo7lQ1hrZyPFcwtjwFP7iEKSHSSJw509kh8kj6pr+H1jR7km9vcvqN9657vffefkv+fKxge1X+7RdjYUPIESN7gTvRkB/RMYtEkaVkdHApmdBPpnKmz0n1xSWFOyVIuLrinZwpoCRe6kyiVZoHX088F+UX4+WKS4iBTP0IWxGtZgOdMaV4KTayqHQF/VihBwTbgDXTCmKoOBJeNhwJMzEVjtjIFLuU38fPR7hqNG1JS7g/qRCuy3vmQ3W9Vu8qbVbP+SzazGRJH83MzP90Ck2m31mMjP8TiLn5uwD2Ugr2PFvPQjB5BnSJvQxGQZZEB+LopqzGzDbMmbkAPkZVJjeO5FzOSBKCgJze2ZS4Gemc9twrwY6u9H61iUQTcRvtdT9RW3tRxAWwFs2tcuJRnI6xjmBdWjbgFNRHMHiF1uHYBfUR/ut5Ug2jXAaT96+9RH/FToRwIzGbKmVJ1AZQnoabSB1yyIg7ByAridHApPMjyw0OiV6RjSbCuzwLAvFizBliWJua1tsuAgvNPbmljYbpt8lkWam7b3XZiOiKJskMOtmfScnsbPW208knwjuXrXK4Q1iKIgNyYXXDVT9C2Ye/78GQ5BEEXfFdde2RwauOysdJNL5AzCy84ard/nGAVN8alecnFdgu5Gbd5DJTL+hHZK0vApVy3OfU8XTSJg1TlssivsPYUlIqvn66PzrVTymCc4wgF6SDNR0pDf+9Gp+VnsUH5WtpHYsuhOaey8zdwLN47V8MTbm78g687+P3cx6tcAeNpjYGRgYGBk8s0/zBIfz2/zlUGeZQNQhOFCWfF0GP0/8P8c1jusIkAuBwMTSBQAYwQM6HjaY2BkYGAV+d8KJgP/XWG9wwAUQQGLAYqPBl942n1TvUoDQRCe1VM8kWARjNrZGIurBAsRBIuA2vkAFsJiKTYW4guIjT5ARMgTxCLoA1hcb5OgDyGHrY7f7M65e8fpLF++2W/nZ2eTmGfaIJi5I0qGDlZZcD51QzTTJirZPAI9JIwVA+wT8L5nOdMaV0AuMJ+icRHq8of6LSD18fzq8ds7xjpwBnQiSI9V5QVl6NwPvgM15NXn/AtWZyj3W0HjEXitOc/dIdbetPdFTZ+P6t+X7xU0/k6GJtOe1/B3arN0/pmz1J4UZc+D6ExwjD7vioeGd5HvhvU+R+DZcGZ6YBPNfAi0G97iBPwFXqph2cW8+D7kjMfwtinHb6kLb6Wygk3cZytSEoptGrlScdHtLPeri1JKueACMZfU1ViJG1Sq5E43dIt7SZZFl1zuRhb/GOs44xFVDbrJzB5tYs35OmaXTrEmkv0DajnMWQB42mNgYNCCwk0MLxheMPrhgUuY2JiUmOqY2pjWMD1hdmPOY+5hPsLCwWLEksSyiOUOawzrLrYiti/sCuxJ7Kc45DiSOPZxmnG2cG7jvMelweXDNYXrEbcBdxf3KR4OngheLd443g18fHwZfFv4NfiX8T8TEBIIEZggsEpQS7BMcJsQl5CFUI3QAWEp4RLhCyJaIldEbURXiJ4RYxEzE0sQ2yD2TzxIfJkEk4SeRJbENIkNEg8k/klqSGZITpE8InlL8p2UmVSG1A6pb9Jx0ltkjGSmyDySlZF1kc2RnSK7R/aZnJ5cmdwB+ST5SwpuCvsUjRTLFHcoOShNU9qhzKespGyhXKV8SPmBCpOKgUqcyjSVR6omqgmqe9RE1OrUnqkHqO9R/6FholGgsUZzgeYZLTUtL60WbS7tKh0OnQydXTpvdGV0O3S/6Gnopekt0ruhz6fvpl+nv0n/h4GdQYvBJUMhwwTDdYYvjFSM4oxmGd0zVjK2M84w3mYiYZJgssLkkqmO6TzTF2Z2ZjVmd8ylzP3MJ5lfsRCwcLJoszhhyWXpZdlhecZKxirHapbVPesF1ndsJGwCbBbZ/LA1sn1jZ2XXY3fFXsM+z36V/S8HD4cGh2OOTI51ThJOK5zeOUs4OzmXOS9wPuUi4JLgss7lm2uU6zY3NrcSty1u39zN3Mvct7l/8xDzMPLw88jyaPM44ynkaeEZ59niucqLyUvPKwgAn3OqOQAAAQAAARcApwARAAAAAAACAAAAAQABAAAAQAAuAAAAAHjarZK9TgJBEMf/d6CRaAyRhMLqCgsbL4ciglTGRPEjSiSKlnLycXJ86CEniU/hM9jYWPgIFkYfwd6nsDD+d1mBIIUx3mZnfzs3MzszuwDCeIYG8UUwQxmAFgxxPeeuyxrmcaNYxzTuFAewi0fFQSTxqXgM11pC8TgS2oPiCUS1d8Uh8ofiSczpYcVT5LjiCPlY8Qui+ncOr7D02y6/BTCrP/m+b5bdTrPi2I26Z9qNGtbRQBMdXMJBGRW0YOCecxEWYoiTCvxrYBunqHPdoX2bLOyrMKlZg8thDETw5K7Itci1TXlGy0124QRZZLDFU/exhxztMozlosTpMH6ZPge0L+OKGnFKjJ4WRwppHPL0PP3SI2P9jLQwFOu3GRhDfkeyDo//G7IHgzllZQxLdquvrdCyBVvat3seJlYo06gxapUxhU2JWnFygR03sSxnEkvcpf5Y5eibGq315TDp7fKWm8zbUVl71Aqq/ZtNnlkWmLnQtno9ycvXYbA6W2pF3aKfCayyC0Ja7Fr/PW70/HO4YM0OKxFvzf0C1MyPjwAAeNpt1VWUU2cYRuHsgxenQt1d8/3JOUnqAyR1d/cCLQVKO22pu7tQd3d3d3d3d3cXmGzumrWy3pWLs/NdPDMpZaWu1783l1Lpf14MnfzO6FbqVupfGkD30iR60JNe9KYP09CXfvRnAAMZxGCGMG3pW6ZjemZgKDMyEzMzC7MyG7MzB3MyF3MzD/MyH/OzAAuyEAuzCIuyGIuzBGWCRIUqOQU16jRYkqVYmmVYluVYng6GMZwRNGmxAiuyEiuzCquyGquzBmuyFmuzDuuyHuuzARuyERuzCZuyGZuzBVuyFVuzDduyHdszklGMZgd2ZAw7MZZxjGdnJrALu9LJbuzOHkxkT/Zib/ZhX/Zjfw7gQA7iYA7hUA7jcI7gSI7iaI7hWI7jeE7gRE7iZE5hEqdyGqdzBmdyFmdzDudyHudzARdyERdzCZdyGZdzBVdyFVdzDddyHddzAzdyEzdzC7dyG7dzB3dyF3dzD/dyH/fzAA/yEA/zCI/yGI/zBE/yFE/zDM/yHM/zAi/yEi/zCq/yGq/zBm/yFm/zDu/yHu/zAR/yER/zCZ/yGZ/zBV/yFV/zDd/yHd/zAz/yEz/zC7/yG7/zB3/yF3/zD/9mpYwsy7pl3bMeWc+sV9Y765NNk/XN+mX9swHZwGxQNjgb0nPkmInjR0V7Uq/OsaPL5Y7ylE3l8tQNN7kVt+rmbuHW3LrbcDvam1rtzVvdm50TxrU/DBvRtZUY1rV5a3jXFn550Wo/XDNWK3dFmh7X9LimxzU9qulRTY9qelTTo5rlKLt2wk7YiaprL+yFvbAX9pK9ZC/ZS/aSvWQv2Uv2kr1kr2KvYq9ir2KvYq9ir2KvYq9ir2Kvaq9qr2qvaq9qr2qvaq9qr2qvai+3l9vL7eX2cnu5vdxebi+3l9sr7BV2CjuFncJOYaewU9gp7NTs1LyrZq9mr2avZq9mr2avZq9mr26vbq9ur26vbq9ur26vbq9ur26vYa9hr2GvYa9hr2GvYa/R7oXuQ/eh+2j/UU7e3C3cqc/V3fYdof/Qf+g/9B/6D/2H/kP/of/Qf+g/9B/6D/2H/kP/of/Qf+g/9B/6D/2H/kP/of/Qf+g/9B/6D/2H/kP/of/Qf+g/9B/6D92H7kP3ofvQfeg+dB+6D92H7kP3ofvQfRT29B/6D/2H/kP/of/Qf+g/9B/6D/2H/kP/of/Qf+g/9B/6D/2H/kP/of/Qf+g/9B/6D/2H/kP/of/Qf+g/9B/6j6nuG3Ya7U5q/0hN3nCTW3Grbu4Wrs/rP+k/6T/pP+k/6T/pP+k+6T7pPek86TzpPOk86TzpOuk66TrpOuk66TrpOlWmPu/36zrpOuk66TrpOuk66TrpOvl/Pek76TvpO+k76TvpO+k76TvpO+k76TvpO7V9t+qtVs/OaOURU6bo6PgPt6rZbwAAAAABVFDDFwAA) format('woff'),url(data:font/ttf;base64,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) format('truetype'),url(data:image/svg+xml;base64,<?xml version="1.0" standalone="no"?>
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd" >
<svg xmlns="http://www.w3.org/2000/svg">
<metadata></metadata>
<defs>
<font id="glyphicons_halflingsregular" horiz-adv-x="1200" >
<font-face units-per-em="1200" ascent="960" descent="-240" />
<missing-glyph horiz-adv-x="500" />
<glyph horiz-adv-x="0" />
<glyph horiz-adv-x="400" />
<glyph unicode=" " />
<glyph unicode="*" d="M600 1100q15 0 34 -1.5t30 -3.5l11 -1q10 -2 17.5 -10.5t7.5 -18.5v-224l158 158q7 7 18 8t19 -6l106 -106q7 -8 6 -19t-8 -18l-158 -158h224q10 0 18.5 -7.5t10.5 -17.5q6 -41 6 -75q0 -15 -1.5 -34t-3.5 -30l-1 -11q-2 -10 -10.5 -17.5t-18.5 -7.5h-224l158 -158 q7 -7 8 -18t-6 -19l-106 -106q-8 -7 -19 -6t-18 8l-158 158v-224q0 -10 -7.5 -18.5t-17.5 -10.5q-41 -6 -75 -6q-15 0 -34 1.5t-30 3.5l-11 1q-10 2 -17.5 10.5t-7.5 18.5v224l-158 -158q-7 -7 -18 -8t-19 6l-106 106q-7 8 -6 19t8 18l158 158h-224q-10 0 -18.5 7.5 t-10.5 17.5q-6 41 -6 75q0 15 1.5 34t3.5 30l1 11q2 10 10.5 17.5t18.5 7.5h224l-158 158q-7 7 -8 18t6 19l106 106q8 7 19 6t18 -8l158 -158v224q0 10 7.5 18.5t17.5 10.5q41 6 75 6z" />
<glyph unicode="+" d="M450 1100h200q21 0 35.5 -14.5t14.5 -35.5v-350h350q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-350v-350q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v350h-350q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5 h350v350q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xa0;" />
<glyph unicode="&#xa5;" d="M825 1100h250q10 0 12.5 -5t-5.5 -13l-364 -364q-6 -6 -11 -18h268q10 0 13 -6t-3 -14l-120 -160q-6 -8 -18 -14t-22 -6h-125v-100h275q10 0 13 -6t-3 -14l-120 -160q-6 -8 -18 -14t-22 -6h-125v-174q0 -11 -7.5 -18.5t-18.5 -7.5h-148q-11 0 -18.5 7.5t-7.5 18.5v174 h-275q-10 0 -13 6t3 14l120 160q6 8 18 14t22 6h125v100h-275q-10 0 -13 6t3 14l120 160q6 8 18 14t22 6h118q-5 12 -11 18l-364 364q-8 8 -5.5 13t12.5 5h250q25 0 43 -18l164 -164q8 -8 18 -8t18 8l164 164q18 18 43 18z" />
<glyph unicode="&#x2000;" horiz-adv-x="650" />
<glyph unicode="&#x2001;" horiz-adv-x="1300" />
<glyph unicode="&#x2002;" horiz-adv-x="650" />
<glyph unicode="&#x2003;" horiz-adv-x="1300" />
<glyph unicode="&#x2004;" horiz-adv-x="433" />
<glyph unicode="&#x2005;" horiz-adv-x="325" />
<glyph unicode="&#x2006;" horiz-adv-x="216" />
<glyph unicode="&#x2007;" horiz-adv-x="216" />
<glyph unicode="&#x2008;" horiz-adv-x="162" />
<glyph unicode="&#x2009;" horiz-adv-x="260" />
<glyph unicode="&#x200a;" horiz-adv-x="72" />
<glyph unicode="&#x202f;" horiz-adv-x="260" />
<glyph unicode="&#x205f;" horiz-adv-x="325" />
<glyph unicode="&#x20ac;" d="M744 1198q242 0 354 -189q60 -104 66 -209h-181q0 45 -17.5 82.5t-43.5 61.5t-58 40.5t-60.5 24t-51.5 7.5q-19 0 -40.5 -5.5t-49.5 -20.5t-53 -38t-49 -62.5t-39 -89.5h379l-100 -100h-300q-6 -50 -6 -100h406l-100 -100h-300q9 -74 33 -132t52.5 -91t61.5 -54.5t59 -29 t47 -7.5q22 0 50.5 7.5t60.5 24.5t58 41t43.5 61t17.5 80h174q-30 -171 -128 -278q-107 -117 -274 -117q-206 0 -324 158q-36 48 -69 133t-45 204h-217l100 100h112q1 47 6 100h-218l100 100h134q20 87 51 153.5t62 103.5q117 141 297 141z" />
<glyph unicode="&#x20bd;" d="M428 1200h350q67 0 120 -13t86 -31t57 -49.5t35 -56.5t17 -64.5t6.5 -60.5t0.5 -57v-16.5v-16.5q0 -36 -0.5 -57t-6.5 -61t-17 -65t-35 -57t-57 -50.5t-86 -31.5t-120 -13h-178l-2 -100h288q10 0 13 -6t-3 -14l-120 -160q-6 -8 -18 -14t-22 -6h-138v-175q0 -11 -5.5 -18 t-15.5 -7h-149q-10 0 -17.5 7.5t-7.5 17.5v175h-267q-10 0 -13 6t3 14l120 160q6 8 18 14t22 6h117v100h-267q-10 0 -13 6t3 14l120 160q6 8 18 14t22 6h117v475q0 10 7.5 17.5t17.5 7.5zM600 1000v-300h203q64 0 86.5 33t22.5 119q0 84 -22.5 116t-86.5 32h-203z" />
<glyph unicode="&#x2212;" d="M250 700h800q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-800q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#x231b;" d="M1000 1200v-150q0 -21 -14.5 -35.5t-35.5 -14.5h-50v-100q0 -91 -49.5 -165.5t-130.5 -109.5q81 -35 130.5 -109.5t49.5 -165.5v-150h50q21 0 35.5 -14.5t14.5 -35.5v-150h-800v150q0 21 14.5 35.5t35.5 14.5h50v150q0 91 49.5 165.5t130.5 109.5q-81 35 -130.5 109.5 t-49.5 165.5v100h-50q-21 0 -35.5 14.5t-14.5 35.5v150h800zM400 1000v-100q0 -60 32.5 -109.5t87.5 -73.5q28 -12 44 -37t16 -55t-16 -55t-44 -37q-55 -24 -87.5 -73.5t-32.5 -109.5v-150h400v150q0 60 -32.5 109.5t-87.5 73.5q-28 12 -44 37t-16 55t16 55t44 37 q55 24 87.5 73.5t32.5 109.5v100h-400z" />
<glyph unicode="&#x25fc;" horiz-adv-x="500" d="M0 0z" />
<glyph unicode="&#x2601;" d="M503 1089q110 0 200.5 -59.5t134.5 -156.5q44 14 90 14q120 0 205 -86.5t85 -206.5q0 -121 -85 -207.5t-205 -86.5h-750q-79 0 -135.5 57t-56.5 137q0 69 42.5 122.5t108.5 67.5q-2 12 -2 37q0 153 108 260.5t260 107.5z" />
<glyph unicode="&#x26fa;" d="M774 1193.5q16 -9.5 20.5 -27t-5.5 -33.5l-136 -187l467 -746h30q20 0 35 -18.5t15 -39.5v-42h-1200v42q0 21 15 39.5t35 18.5h30l468 746l-135 183q-10 16 -5.5 34t20.5 28t34 5.5t28 -20.5l111 -148l112 150q9 16 27 20.5t34 -5zM600 200h377l-182 112l-195 534v-646z " />
<glyph unicode="&#x2709;" d="M25 1100h1150q10 0 12.5 -5t-5.5 -13l-564 -567q-8 -8 -18 -8t-18 8l-564 567q-8 8 -5.5 13t12.5 5zM18 882l264 -264q8 -8 8 -18t-8 -18l-264 -264q-8 -8 -13 -5.5t-5 12.5v550q0 10 5 12.5t13 -5.5zM918 618l264 264q8 8 13 5.5t5 -12.5v-550q0 -10 -5 -12.5t-13 5.5 l-264 264q-8 8 -8 18t8 18zM818 482l364 -364q8 -8 5.5 -13t-12.5 -5h-1150q-10 0 -12.5 5t5.5 13l364 364q8 8 18 8t18 -8l164 -164q8 -8 18 -8t18 8l164 164q8 8 18 8t18 -8z" />
<glyph unicode="&#x270f;" d="M1011 1210q19 0 33 -13l153 -153q13 -14 13 -33t-13 -33l-99 -92l-214 214l95 96q13 14 32 14zM1013 800l-615 -614l-214 214l614 614zM317 96l-333 -112l110 335z" />
<glyph unicode="&#xe001;" d="M700 650v-550h250q21 0 35.5 -14.5t14.5 -35.5v-50h-800v50q0 21 14.5 35.5t35.5 14.5h250v550l-500 550h1200z" />
<glyph unicode="&#xe002;" d="M368 1017l645 163q39 15 63 0t24 -49v-831q0 -55 -41.5 -95.5t-111.5 -63.5q-79 -25 -147 -4.5t-86 75t25.5 111.5t122.5 82q72 24 138 8v521l-600 -155v-606q0 -42 -44 -90t-109 -69q-79 -26 -147 -5.5t-86 75.5t25.5 111.5t122.5 82.5q72 24 138 7v639q0 38 14.5 59 t53.5 34z" />
<glyph unicode="&#xe003;" d="M500 1191q100 0 191 -39t156.5 -104.5t104.5 -156.5t39 -191l-1 -2l1 -5q0 -141 -78 -262l275 -274q23 -26 22.5 -44.5t-22.5 -42.5l-59 -58q-26 -20 -46.5 -20t-39.5 20l-275 274q-119 -77 -261 -77l-5 1l-2 -1q-100 0 -191 39t-156.5 104.5t-104.5 156.5t-39 191 t39 191t104.5 156.5t156.5 104.5t191 39zM500 1022q-88 0 -162 -43t-117 -117t-43 -162t43 -162t117 -117t162 -43t162 43t117 117t43 162t-43 162t-117 117t-162 43z" />
<glyph unicode="&#xe005;" d="M649 949q48 68 109.5 104t121.5 38.5t118.5 -20t102.5 -64t71 -100.5t27 -123q0 -57 -33.5 -117.5t-94 -124.5t-126.5 -127.5t-150 -152.5t-146 -174q-62 85 -145.5 174t-150 152.5t-126.5 127.5t-93.5 124.5t-33.5 117.5q0 64 28 123t73 100.5t104 64t119 20 t120.5 -38.5t104.5 -104z" />
<glyph unicode="&#xe006;" d="M407 800l131 353q7 19 17.5 19t17.5 -19l129 -353h421q21 0 24 -8.5t-14 -20.5l-342 -249l130 -401q7 -20 -0.5 -25.5t-24.5 6.5l-343 246l-342 -247q-17 -12 -24.5 -6.5t-0.5 25.5l130 400l-347 251q-17 12 -14 20.5t23 8.5h429z" />
<glyph unicode="&#xe007;" d="M407 800l131 353q7 19 17.5 19t17.5 -19l129 -353h421q21 0 24 -8.5t-14 -20.5l-342 -249l130 -401q7 -20 -0.5 -25.5t-24.5 6.5l-343 246l-342 -247q-17 -12 -24.5 -6.5t-0.5 25.5l130 400l-347 251q-17 12 -14 20.5t23 8.5h429zM477 700h-240l197 -142l-74 -226 l193 139l195 -140l-74 229l192 140h-234l-78 211z" />
<glyph unicode="&#xe008;" d="M600 1200q124 0 212 -88t88 -212v-250q0 -46 -31 -98t-69 -52v-75q0 -10 6 -21.5t15 -17.5l358 -230q9 -5 15 -16.5t6 -21.5v-93q0 -10 -7.5 -17.5t-17.5 -7.5h-1150q-10 0 -17.5 7.5t-7.5 17.5v93q0 10 6 21.5t15 16.5l358 230q9 6 15 17.5t6 21.5v75q-38 0 -69 52 t-31 98v250q0 124 88 212t212 88z" />
<glyph unicode="&#xe009;" d="M25 1100h1150q10 0 17.5 -7.5t7.5 -17.5v-1050q0 -10 -7.5 -17.5t-17.5 -7.5h-1150q-10 0 -17.5 7.5t-7.5 17.5v1050q0 10 7.5 17.5t17.5 7.5zM100 1000v-100h100v100h-100zM875 1000h-550q-10 0 -17.5 -7.5t-7.5 -17.5v-350q0 -10 7.5 -17.5t17.5 -7.5h550 q10 0 17.5 7.5t7.5 17.5v350q0 10 -7.5 17.5t-17.5 7.5zM1000 1000v-100h100v100h-100zM100 800v-100h100v100h-100zM1000 800v-100h100v100h-100zM100 600v-100h100v100h-100zM1000 600v-100h100v100h-100zM875 500h-550q-10 0 -17.5 -7.5t-7.5 -17.5v-350q0 -10 7.5 -17.5 t17.5 -7.5h550q10 0 17.5 7.5t7.5 17.5v350q0 10 -7.5 17.5t-17.5 7.5zM100 400v-100h100v100h-100zM1000 400v-100h100v100h-100zM100 200v-100h100v100h-100zM1000 200v-100h100v100h-100z" />
<glyph unicode="&#xe010;" d="M50 1100h400q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5zM650 1100h400q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-21 0 -35.5 14.5t-14.5 35.5v400 q0 21 14.5 35.5t35.5 14.5zM50 500h400q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5zM650 500h400q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-400 q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe011;" d="M50 1100h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM450 1100h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200 q0 21 14.5 35.5t35.5 14.5zM850 1100h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM50 700h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200 q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM450 700h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM850 700h200q21 0 35.5 -14.5t14.5 -35.5v-200 q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM50 300h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM450 300h200 q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM850 300h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5 t35.5 14.5z" />
<glyph unicode="&#xe012;" d="M50 1100h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM450 1100h700q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-700q-21 0 -35.5 14.5t-14.5 35.5v200 q0 21 14.5 35.5t35.5 14.5zM50 700h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM450 700h700q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-700 q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM50 300h200q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5zM450 300h700q21 0 35.5 -14.5t14.5 -35.5v-200 q0 -21 -14.5 -35.5t-35.5 -14.5h-700q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe013;" d="M465 477l571 571q8 8 18 8t17 -8l177 -177q8 -7 8 -17t-8 -18l-783 -784q-7 -8 -17.5 -8t-17.5 8l-384 384q-8 8 -8 18t8 17l177 177q7 8 17 8t18 -8l171 -171q7 -7 18 -7t18 7z" />
<glyph unicode="&#xe014;" d="M904 1083l178 -179q8 -8 8 -18.5t-8 -17.5l-267 -268l267 -268q8 -7 8 -17.5t-8 -18.5l-178 -178q-8 -8 -18.5 -8t-17.5 8l-268 267l-268 -267q-7 -8 -17.5 -8t-18.5 8l-178 178q-8 8 -8 18.5t8 17.5l267 268l-267 268q-8 7 -8 17.5t8 18.5l178 178q8 8 18.5 8t17.5 -8 l268 -267l268 268q7 7 17.5 7t18.5 -7z" />
<glyph unicode="&#xe015;" d="M507 1177q98 0 187.5 -38.5t154.5 -103.5t103.5 -154.5t38.5 -187.5q0 -141 -78 -262l300 -299q8 -8 8 -18.5t-8 -18.5l-109 -108q-7 -8 -17.5 -8t-18.5 8l-300 299q-119 -77 -261 -77q-98 0 -188 38.5t-154.5 103t-103 154.5t-38.5 188t38.5 187.5t103 154.5 t154.5 103.5t188 38.5zM506.5 1023q-89.5 0 -165.5 -44t-120 -120.5t-44 -166t44 -165.5t120 -120t165.5 -44t166 44t120.5 120t44 165.5t-44 166t-120.5 120.5t-166 44zM425 900h150q10 0 17.5 -7.5t7.5 -17.5v-75h75q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5 t-17.5 -7.5h-75v-75q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v75h-75q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5h75v75q0 10 7.5 17.5t17.5 7.5z" />
<glyph unicode="&#xe016;" d="M507 1177q98 0 187.5 -38.5t154.5 -103.5t103.5 -154.5t38.5 -187.5q0 -141 -78 -262l300 -299q8 -8 8 -18.5t-8 -18.5l-109 -108q-7 -8 -17.5 -8t-18.5 8l-300 299q-119 -77 -261 -77q-98 0 -188 38.5t-154.5 103t-103 154.5t-38.5 188t38.5 187.5t103 154.5 t154.5 103.5t188 38.5zM506.5 1023q-89.5 0 -165.5 -44t-120 -120.5t-44 -166t44 -165.5t120 -120t165.5 -44t166 44t120.5 120t44 165.5t-44 166t-120.5 120.5t-166 44zM325 800h350q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-350q-10 0 -17.5 7.5 t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5z" />
<glyph unicode="&#xe017;" d="M550 1200h100q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5zM800 975v166q167 -62 272 -209.5t105 -331.5q0 -117 -45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5 t-184.5 123t-123 184.5t-45.5 224q0 184 105 331.5t272 209.5v-166q-103 -55 -165 -155t-62 -220q0 -116 57 -214.5t155.5 -155.5t214.5 -57t214.5 57t155.5 155.5t57 214.5q0 120 -62 220t-165 155z" />
<glyph unicode="&#xe018;" d="M1025 1200h150q10 0 17.5 -7.5t7.5 -17.5v-1150q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v1150q0 10 7.5 17.5t17.5 7.5zM725 800h150q10 0 17.5 -7.5t7.5 -17.5v-750q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v750 q0 10 7.5 17.5t17.5 7.5zM425 500h150q10 0 17.5 -7.5t7.5 -17.5v-450q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v450q0 10 7.5 17.5t17.5 7.5zM125 300h150q10 0 17.5 -7.5t7.5 -17.5v-250q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5 v250q0 10 7.5 17.5t17.5 7.5z" />
<glyph unicode="&#xe019;" d="M600 1174q33 0 74 -5l38 -152l5 -1q49 -14 94 -39l5 -2l134 80q61 -48 104 -105l-80 -134l3 -5q25 -44 39 -93l1 -6l152 -38q5 -43 5 -73q0 -34 -5 -74l-152 -38l-1 -6q-15 -49 -39 -93l-3 -5l80 -134q-48 -61 -104 -105l-134 81l-5 -3q-44 -25 -94 -39l-5 -2l-38 -151 q-43 -5 -74 -5q-33 0 -74 5l-38 151l-5 2q-49 14 -94 39l-5 3l-134 -81q-60 48 -104 105l80 134l-3 5q-25 45 -38 93l-2 6l-151 38q-6 42 -6 74q0 33 6 73l151 38l2 6q13 48 38 93l3 5l-80 134q47 61 105 105l133 -80l5 2q45 25 94 39l5 1l38 152q43 5 74 5zM600 815 q-89 0 -152 -63t-63 -151.5t63 -151.5t152 -63t152 63t63 151.5t-63 151.5t-152 63z" />
<glyph unicode="&#xe020;" d="M500 1300h300q41 0 70.5 -29.5t29.5 -70.5v-100h275q10 0 17.5 -7.5t7.5 -17.5v-75h-1100v75q0 10 7.5 17.5t17.5 7.5h275v100q0 41 29.5 70.5t70.5 29.5zM500 1200v-100h300v100h-300zM1100 900v-800q0 -41 -29.5 -70.5t-70.5 -29.5h-700q-41 0 -70.5 29.5t-29.5 70.5 v800h900zM300 800v-700h100v700h-100zM500 800v-700h100v700h-100zM700 800v-700h100v700h-100zM900 800v-700h100v700h-100z" />
<glyph unicode="&#xe021;" d="M18 618l620 608q8 7 18.5 7t17.5 -7l608 -608q8 -8 5.5 -13t-12.5 -5h-175v-575q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v375h-300v-375q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v575h-175q-10 0 -12.5 5t5.5 13z" />
<glyph unicode="&#xe022;" d="M600 1200v-400q0 -41 29.5 -70.5t70.5 -29.5h300v-650q0 -21 -14.5 -35.5t-35.5 -14.5h-800q-21 0 -35.5 14.5t-14.5 35.5v1100q0 21 14.5 35.5t35.5 14.5h450zM1000 800h-250q-21 0 -35.5 14.5t-14.5 35.5v250z" />
<glyph unicode="&#xe023;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM600 1027q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5t57 -214.5 t155.5 -155.5t214.5 -57t214.5 57t155.5 155.5t57 214.5t-57 214.5t-155.5 155.5t-214.5 57zM525 900h50q10 0 17.5 -7.5t7.5 -17.5v-275h175q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v350q0 10 7.5 17.5t17.5 7.5z" />
<glyph unicode="&#xe024;" d="M1300 0h-538l-41 400h-242l-41 -400h-538l431 1200h209l-21 -300h162l-20 300h208zM515 800l-27 -300h224l-27 300h-170z" />
<glyph unicode="&#xe025;" d="M550 1200h200q21 0 35.5 -14.5t14.5 -35.5v-450h191q20 0 25.5 -11.5t-7.5 -27.5l-327 -400q-13 -16 -32 -16t-32 16l-327 400q-13 16 -7.5 27.5t25.5 11.5h191v450q0 21 14.5 35.5t35.5 14.5zM1125 400h50q10 0 17.5 -7.5t7.5 -17.5v-350q0 -10 -7.5 -17.5t-17.5 -7.5 h-1050q-10 0 -17.5 7.5t-7.5 17.5v350q0 10 7.5 17.5t17.5 7.5h50q10 0 17.5 -7.5t7.5 -17.5v-175h900v175q0 10 7.5 17.5t17.5 7.5z" />
<glyph unicode="&#xe026;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM600 1027q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5t57 -214.5 t155.5 -155.5t214.5 -57t214.5 57t155.5 155.5t57 214.5t-57 214.5t-155.5 155.5t-214.5 57zM525 900h150q10 0 17.5 -7.5t7.5 -17.5v-275h137q21 0 26 -11.5t-8 -27.5l-223 -275q-13 -16 -32 -16t-32 16l-223 275q-13 16 -8 27.5t26 11.5h137v275q0 10 7.5 17.5t17.5 7.5z " />
<glyph unicode="&#xe027;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM600 1027q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5t57 -214.5 t155.5 -155.5t214.5 -57t214.5 57t155.5 155.5t57 214.5t-57 214.5t-155.5 155.5t-214.5 57zM632 914l223 -275q13 -16 8 -27.5t-26 -11.5h-137v-275q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v275h-137q-21 0 -26 11.5t8 27.5l223 275q13 16 32 16 t32 -16z" />
<glyph unicode="&#xe028;" d="M225 1200h750q10 0 19.5 -7t12.5 -17l186 -652q7 -24 7 -49v-425q0 -12 -4 -27t-9 -17q-12 -6 -37 -6h-1100q-12 0 -27 4t-17 8q-6 13 -6 38l1 425q0 25 7 49l185 652q3 10 12.5 17t19.5 7zM878 1000h-556q-10 0 -19 -7t-11 -18l-87 -450q-2 -11 4 -18t16 -7h150 q10 0 19.5 -7t11.5 -17l38 -152q2 -10 11.5 -17t19.5 -7h250q10 0 19.5 7t11.5 17l38 152q2 10 11.5 17t19.5 7h150q10 0 16 7t4 18l-87 450q-2 11 -11 18t-19 7z" />
<glyph unicode="&#xe029;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM600 1027q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5t57 -214.5 t155.5 -155.5t214.5 -57t214.5 57t155.5 155.5t57 214.5t-57 214.5t-155.5 155.5t-214.5 57zM540 820l253 -190q17 -12 17 -30t-17 -30l-253 -190q-16 -12 -28 -6.5t-12 26.5v400q0 21 12 26.5t28 -6.5z" />
<glyph unicode="&#xe030;" d="M947 1060l135 135q7 7 12.5 5t5.5 -13v-362q0 -10 -7.5 -17.5t-17.5 -7.5h-362q-11 0 -13 5.5t5 12.5l133 133q-109 76 -238 76q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5t57 -214.5t155.5 -155.5t214.5 -57t214.5 57t155.5 155.5t57 214.5h150q0 -117 -45.5 -224 t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5q192 0 347 -117z" />
<glyph unicode="&#xe031;" d="M947 1060l135 135q7 7 12.5 5t5.5 -13v-361q0 -11 -7.5 -18.5t-18.5 -7.5h-361q-11 0 -13 5.5t5 12.5l134 134q-110 75 -239 75q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5h-150q0 117 45.5 224t123 184.5t184.5 123t224 45.5q192 0 347 -117zM1027 600h150 q0 -117 -45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5q-192 0 -348 118l-134 -134q-7 -8 -12.5 -5.5t-5.5 12.5v360q0 11 7.5 18.5t18.5 7.5h360q10 0 12.5 -5.5t-5.5 -12.5l-133 -133q110 -76 240 -76q116 0 214.5 57t155.5 155.5t57 214.5z" />
<glyph unicode="&#xe032;" d="M125 1200h1050q10 0 17.5 -7.5t7.5 -17.5v-1150q0 -10 -7.5 -17.5t-17.5 -7.5h-1050q-10 0 -17.5 7.5t-7.5 17.5v1150q0 10 7.5 17.5t17.5 7.5zM1075 1000h-850q-10 0 -17.5 -7.5t-7.5 -17.5v-850q0 -10 7.5 -17.5t17.5 -7.5h850q10 0 17.5 7.5t7.5 17.5v850 q0 10 -7.5 17.5t-17.5 7.5zM325 900h50q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-50q-10 0 -17.5 7.5t-7.5 17.5v50q0 10 7.5 17.5t17.5 7.5zM525 900h450q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-450q-10 0 -17.5 7.5t-7.5 17.5v50 q0 10 7.5 17.5t17.5 7.5zM325 700h50q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-50q-10 0 -17.5 7.5t-7.5 17.5v50q0 10 7.5 17.5t17.5 7.5zM525 700h450q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-450q-10 0 -17.5 7.5t-7.5 17.5v50 q0 10 7.5 17.5t17.5 7.5zM325 500h50q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-50q-10 0 -17.5 7.5t-7.5 17.5v50q0 10 7.5 17.5t17.5 7.5zM525 500h450q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-450q-10 0 -17.5 7.5t-7.5 17.5v50 q0 10 7.5 17.5t17.5 7.5zM325 300h50q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-50q-10 0 -17.5 7.5t-7.5 17.5v50q0 10 7.5 17.5t17.5 7.5zM525 300h450q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-450q-10 0 -17.5 7.5t-7.5 17.5v50 q0 10 7.5 17.5t17.5 7.5z" />
<glyph unicode="&#xe033;" d="M900 800v200q0 83 -58.5 141.5t-141.5 58.5h-300q-82 0 -141 -59t-59 -141v-200h-100q-41 0 -70.5 -29.5t-29.5 -70.5v-600q0 -41 29.5 -70.5t70.5 -29.5h900q41 0 70.5 29.5t29.5 70.5v600q0 41 -29.5 70.5t-70.5 29.5h-100zM400 800v150q0 21 15 35.5t35 14.5h200 q20 0 35 -14.5t15 -35.5v-150h-300z" />
<glyph unicode="&#xe034;" d="M125 1100h50q10 0 17.5 -7.5t7.5 -17.5v-1075h-100v1075q0 10 7.5 17.5t17.5 7.5zM1075 1052q4 0 9 -2q16 -6 16 -23v-421q0 -6 -3 -12q-33 -59 -66.5 -99t-65.5 -58t-56.5 -24.5t-52.5 -6.5q-26 0 -57.5 6.5t-52.5 13.5t-60 21q-41 15 -63 22.5t-57.5 15t-65.5 7.5 q-85 0 -160 -57q-7 -5 -15 -5q-6 0 -11 3q-14 7 -14 22v438q22 55 82 98.5t119 46.5q23 2 43 0.5t43 -7t32.5 -8.5t38 -13t32.5 -11q41 -14 63.5 -21t57 -14t63.5 -7q103 0 183 87q7 8 18 8z" />
<glyph unicode="&#xe035;" d="M600 1175q116 0 227 -49.5t192.5 -131t131 -192.5t49.5 -227v-300q0 -10 -7.5 -17.5t-17.5 -7.5h-50q-10 0 -17.5 7.5t-7.5 17.5v300q0 127 -70.5 231.5t-184.5 161.5t-245 57t-245 -57t-184.5 -161.5t-70.5 -231.5v-300q0 -10 -7.5 -17.5t-17.5 -7.5h-50 q-10 0 -17.5 7.5t-7.5 17.5v300q0 116 49.5 227t131 192.5t192.5 131t227 49.5zM220 500h160q8 0 14 -6t6 -14v-460q0 -8 -6 -14t-14 -6h-160q-8 0 -14 6t-6 14v460q0 8 6 14t14 6zM820 500h160q8 0 14 -6t6 -14v-460q0 -8 -6 -14t-14 -6h-160q-8 0 -14 6t-6 14v460 q0 8 6 14t14 6z" />
<glyph unicode="&#xe036;" d="M321 814l258 172q9 6 15 2.5t6 -13.5v-750q0 -10 -6 -13.5t-15 2.5l-258 172q-21 14 -46 14h-250q-10 0 -17.5 7.5t-7.5 17.5v350q0 10 7.5 17.5t17.5 7.5h250q25 0 46 14zM900 668l120 120q7 7 17 7t17 -7l34 -34q7 -7 7 -17t-7 -17l-120 -120l120 -120q7 -7 7 -17 t-7 -17l-34 -34q-7 -7 -17 -7t-17 7l-120 119l-120 -119q-7 -7 -17 -7t-17 7l-34 34q-7 7 -7 17t7 17l119 120l-119 120q-7 7 -7 17t7 17l34 34q7 8 17 8t17 -8z" />
<glyph unicode="&#xe037;" d="M321 814l258 172q9 6 15 2.5t6 -13.5v-750q0 -10 -6 -13.5t-15 2.5l-258 172q-21 14 -46 14h-250q-10 0 -17.5 7.5t-7.5 17.5v350q0 10 7.5 17.5t17.5 7.5h250q25 0 46 14zM766 900h4q10 -1 16 -10q96 -129 96 -290q0 -154 -90 -281q-6 -9 -17 -10l-3 -1q-9 0 -16 6 l-29 23q-7 7 -8.5 16.5t4.5 17.5q72 103 72 229q0 132 -78 238q-6 8 -4.5 18t9.5 17l29 22q7 5 15 5z" />
<glyph unicode="&#xe038;" d="M967 1004h3q11 -1 17 -10q135 -179 135 -396q0 -105 -34 -206.5t-98 -185.5q-7 -9 -17 -10h-3q-9 0 -16 6l-42 34q-8 6 -9 16t5 18q111 150 111 328q0 90 -29.5 176t-84.5 157q-6 9 -5 19t10 16l42 33q7 5 15 5zM321 814l258 172q9 6 15 2.5t6 -13.5v-750q0 -10 -6 -13.5 t-15 2.5l-258 172q-21 14 -46 14h-250q-10 0 -17.5 7.5t-7.5 17.5v350q0 10 7.5 17.5t17.5 7.5h250q25 0 46 14zM766 900h4q10 -1 16 -10q96 -129 96 -290q0 -154 -90 -281q-6 -9 -17 -10l-3 -1q-9 0 -16 6l-29 23q-7 7 -8.5 16.5t4.5 17.5q72 103 72 229q0 132 -78 238 q-6 8 -4.5 18.5t9.5 16.5l29 22q7 5 15 5z" />
<glyph unicode="&#xe039;" d="M500 900h100v-100h-100v-100h-400v-100h-100v600h500v-300zM1200 700h-200v-100h200v-200h-300v300h-200v300h-100v200h600v-500zM100 1100v-300h300v300h-300zM800 1100v-300h300v300h-300zM300 900h-100v100h100v-100zM1000 900h-100v100h100v-100zM300 500h200v-500 h-500v500h200v100h100v-100zM800 300h200v-100h-100v-100h-200v100h-100v100h100v200h-200v100h300v-300zM100 400v-300h300v300h-300zM300 200h-100v100h100v-100zM1200 200h-100v100h100v-100zM700 0h-100v100h100v-100zM1200 0h-300v100h300v-100z" />
<glyph unicode="&#xe040;" d="M100 200h-100v1000h100v-1000zM300 200h-100v1000h100v-1000zM700 200h-200v1000h200v-1000zM900 200h-100v1000h100v-1000zM1200 200h-200v1000h200v-1000zM400 0h-300v100h300v-100zM600 0h-100v91h100v-91zM800 0h-100v91h100v-91zM1100 0h-200v91h200v-91z" />
<glyph unicode="&#xe041;" d="M500 1200l682 -682q8 -8 8 -18t-8 -18l-464 -464q-8 -8 -18 -8t-18 8l-682 682l1 475q0 10 7.5 17.5t17.5 7.5h474zM319.5 1024.5q-29.5 29.5 -71 29.5t-71 -29.5t-29.5 -71.5t29.5 -71.5t71 -29.5t71 29.5t29.5 71.5t-29.5 71.5z" />
<glyph unicode="&#xe042;" d="M500 1200l682 -682q8 -8 8 -18t-8 -18l-464 -464q-8 -8 -18 -8t-18 8l-682 682l1 475q0 10 7.5 17.5t17.5 7.5h474zM800 1200l682 -682q8 -8 8 -18t-8 -18l-464 -464q-8 -8 -18 -8t-18 8l-56 56l424 426l-700 700h150zM319.5 1024.5q-29.5 29.5 -71 29.5t-71 -29.5 t-29.5 -71.5t29.5 -71.5t71 -29.5t71 29.5t29.5 71.5t-29.5 71.5z" />
<glyph unicode="&#xe043;" d="M300 1200h825q75 0 75 -75v-900q0 -25 -18 -43l-64 -64q-8 -8 -13 -5.5t-5 12.5v950q0 10 -7.5 17.5t-17.5 7.5h-700q-25 0 -43 -18l-64 -64q-8 -8 -5.5 -13t12.5 -5h700q10 0 17.5 -7.5t7.5 -17.5v-950q0 -10 -7.5 -17.5t-17.5 -7.5h-850q-10 0 -17.5 7.5t-7.5 17.5v975 q0 25 18 43l139 139q18 18 43 18z" />
<glyph unicode="&#xe044;" d="M250 1200h800q21 0 35.5 -14.5t14.5 -35.5v-1150l-450 444l-450 -445v1151q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe045;" d="M822 1200h-444q-11 0 -19 -7.5t-9 -17.5l-78 -301q-7 -24 7 -45l57 -108q6 -9 17.5 -15t21.5 -6h450q10 0 21.5 6t17.5 15l62 108q14 21 7 45l-83 301q-1 10 -9 17.5t-19 7.5zM1175 800h-150q-10 0 -21 -6.5t-15 -15.5l-78 -156q-4 -9 -15 -15.5t-21 -6.5h-550 q-10 0 -21 6.5t-15 15.5l-78 156q-4 9 -15 15.5t-21 6.5h-150q-10 0 -17.5 -7.5t-7.5 -17.5v-650q0 -10 7.5 -17.5t17.5 -7.5h150q10 0 17.5 7.5t7.5 17.5v150q0 10 7.5 17.5t17.5 7.5h750q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 7.5 -17.5t17.5 -7.5h150q10 0 17.5 7.5 t7.5 17.5v650q0 10 -7.5 17.5t-17.5 7.5zM850 200h-500q-10 0 -19.5 -7t-11.5 -17l-38 -152q-2 -10 3.5 -17t15.5 -7h600q10 0 15.5 7t3.5 17l-38 152q-2 10 -11.5 17t-19.5 7z" />
<glyph unicode="&#xe046;" d="M500 1100h200q56 0 102.5 -20.5t72.5 -50t44 -59t25 -50.5l6 -20h150q41 0 70.5 -29.5t29.5 -70.5v-600q0 -41 -29.5 -70.5t-70.5 -29.5h-1000q-41 0 -70.5 29.5t-29.5 70.5v600q0 41 29.5 70.5t70.5 29.5h150q2 8 6.5 21.5t24 48t45 61t72 48t102.5 21.5zM900 800v-100 h100v100h-100zM600 730q-95 0 -162.5 -67.5t-67.5 -162.5t67.5 -162.5t162.5 -67.5t162.5 67.5t67.5 162.5t-67.5 162.5t-162.5 67.5zM600 603q43 0 73 -30t30 -73t-30 -73t-73 -30t-73 30t-30 73t30 73t73 30z" />
<glyph unicode="&#xe047;" d="M681 1199l385 -998q20 -50 60 -92q18 -19 36.5 -29.5t27.5 -11.5l10 -2v-66h-417v66q53 0 75 43.5t5 88.5l-82 222h-391q-58 -145 -92 -234q-11 -34 -6.5 -57t25.5 -37t46 -20t55 -6v-66h-365v66q56 24 84 52q12 12 25 30.5t20 31.5l7 13l399 1006h93zM416 521h340 l-162 457z" />
<glyph unicode="&#xe048;" d="M753 641q5 -1 14.5 -4.5t36 -15.5t50.5 -26.5t53.5 -40t50.5 -54.5t35.5 -70t14.5 -87q0 -67 -27.5 -125.5t-71.5 -97.5t-98.5 -66.5t-108.5 -40.5t-102 -13h-500v89q41 7 70.5 32.5t29.5 65.5v827q0 24 -0.5 34t-3.5 24t-8.5 19.5t-17 13.5t-28 12.5t-42.5 11.5v71 l471 -1q57 0 115.5 -20.5t108 -57t80.5 -94t31 -124.5q0 -51 -15.5 -96.5t-38 -74.5t-45 -50.5t-38.5 -30.5zM400 700h139q78 0 130.5 48.5t52.5 122.5q0 41 -8.5 70.5t-29.5 55.5t-62.5 39.5t-103.5 13.5h-118v-350zM400 200h216q80 0 121 50.5t41 130.5q0 90 -62.5 154.5 t-156.5 64.5h-159v-400z" />
<glyph unicode="&#xe049;" d="M877 1200l2 -57q-83 -19 -116 -45.5t-40 -66.5l-132 -839q-9 -49 13 -69t96 -26v-97h-500v97q186 16 200 98l173 832q3 17 3 30t-1.5 22.5t-9 17.5t-13.5 12.5t-21.5 10t-26 8.5t-33.5 10q-13 3 -19 5v57h425z" />
<glyph unicode="&#xe050;" d="M1300 900h-50q0 21 -4 37t-9.5 26.5t-18 17.5t-22 11t-28.5 5.5t-31 2t-37 0.5h-200v-850q0 -22 25 -34.5t50 -13.5l25 -2v-100h-400v100q4 0 11 0.5t24 3t30 7t24 15t11 24.5v850h-200q-25 0 -37 -0.5t-31 -2t-28.5 -5.5t-22 -11t-18 -17.5t-9.5 -26.5t-4 -37h-50v300 h1000v-300zM175 1000h-75v-800h75l-125 -167l-125 167h75v800h-75l125 167z" />
<glyph unicode="&#xe051;" d="M1100 900h-50q0 21 -4 37t-9.5 26.5t-18 17.5t-22 11t-28.5 5.5t-31 2t-37 0.5h-200v-650q0 -22 25 -34.5t50 -13.5l25 -2v-100h-400v100q4 0 11 0.5t24 3t30 7t24 15t11 24.5v650h-200q-25 0 -37 -0.5t-31 -2t-28.5 -5.5t-22 -11t-18 -17.5t-9.5 -26.5t-4 -37h-50v300 h1000v-300zM1167 50l-167 -125v75h-800v-75l-167 125l167 125v-75h800v75z" />
<glyph unicode="&#xe052;" d="M50 1100h600q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-600q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM50 800h1000q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1000q-21 0 -35.5 14.5t-14.5 35.5v100 q0 21 14.5 35.5t35.5 14.5zM50 500h800q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-800q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM50 200h1100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1100 q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe053;" d="M250 1100h700q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-700q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM50 800h1100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1100q-21 0 -35.5 14.5t-14.5 35.5v100 q0 21 14.5 35.5t35.5 14.5zM250 500h700q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-700q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM50 200h1100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1100 q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe054;" d="M500 950v100q0 21 14.5 35.5t35.5 14.5h600q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-600q-21 0 -35.5 14.5t-14.5 35.5zM100 650v100q0 21 14.5 35.5t35.5 14.5h1000q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1000 q-21 0 -35.5 14.5t-14.5 35.5zM300 350v100q0 21 14.5 35.5t35.5 14.5h800q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-800q-21 0 -35.5 14.5t-14.5 35.5zM0 50v100q0 21 14.5 35.5t35.5 14.5h1100q21 0 35.5 -14.5t14.5 -35.5v-100 q0 -21 -14.5 -35.5t-35.5 -14.5h-1100q-21 0 -35.5 14.5t-14.5 35.5z" />
<glyph unicode="&#xe055;" d="M50 1100h1100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1100q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM50 800h1100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1100q-21 0 -35.5 14.5t-14.5 35.5v100 q0 21 14.5 35.5t35.5 14.5zM50 500h1100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1100q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM50 200h1100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1100 q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe056;" d="M50 1100h100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM350 1100h800q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-800q-21 0 -35.5 14.5t-14.5 35.5v100 q0 21 14.5 35.5t35.5 14.5zM50 800h100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM350 800h800q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-800 q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM50 500h100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM350 500h800q21 0 35.5 -14.5t14.5 -35.5v-100 q0 -21 -14.5 -35.5t-35.5 -14.5h-800q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM50 200h100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM350 200h800 q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-800q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe057;" d="M400 0h-100v1100h100v-1100zM550 1100h100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM550 800h500q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-500 q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM267 550l-167 -125v75h-200v100h200v75zM550 500h300q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-300q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM550 200h600 q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-600q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe058;" d="M50 1100h100q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM900 0h-100v1100h100v-1100zM50 800h500q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-500 q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM1100 600h200v-100h-200v-75l-167 125l167 125v-75zM50 500h300q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-300q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5zM50 200h600 q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-600q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe059;" d="M75 1000h750q31 0 53 -22t22 -53v-650q0 -31 -22 -53t-53 -22h-750q-31 0 -53 22t-22 53v650q0 31 22 53t53 22zM1200 300l-300 300l300 300v-600z" />
<glyph unicode="&#xe060;" d="M44 1100h1112q18 0 31 -13t13 -31v-1012q0 -18 -13 -31t-31 -13h-1112q-18 0 -31 13t-13 31v1012q0 18 13 31t31 13zM100 1000v-737l247 182l298 -131l-74 156l293 318l236 -288v500h-1000zM342 884q56 0 95 -39t39 -94.5t-39 -95t-95 -39.5t-95 39.5t-39 95t39 94.5 t95 39z" />
<glyph unicode="&#xe062;" d="M648 1169q117 0 216 -60t156.5 -161t57.5 -218q0 -115 -70 -258q-69 -109 -158 -225.5t-143 -179.5l-54 -62q-9 8 -25.5 24.5t-63.5 67.5t-91 103t-98.5 128t-95.5 148q-60 132 -60 249q0 88 34 169.5t91.5 142t137 96.5t166.5 36zM652.5 974q-91.5 0 -156.5 -65 t-65 -157t65 -156.5t156.5 -64.5t156.5 64.5t65 156.5t-65 157t-156.5 65z" />
<glyph unicode="&#xe063;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM600 173v854q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5t57 -214.5 t155.5 -155.5t214.5 -57z" />
<glyph unicode="&#xe064;" d="M554 1295q21 -72 57.5 -143.5t76 -130t83 -118t82.5 -117t70 -116t49.5 -126t18.5 -136.5q0 -71 -25.5 -135t-68.5 -111t-99 -82t-118.5 -54t-125.5 -23q-84 5 -161.5 34t-139.5 78.5t-99 125t-37 164.5q0 69 18 136.5t49.5 126.5t69.5 116.5t81.5 117.5t83.5 119 t76.5 131t58.5 143zM344 710q-23 -33 -43.5 -70.5t-40.5 -102.5t-17 -123q1 -37 14.5 -69.5t30 -52t41 -37t38.5 -24.5t33 -15q21 -7 32 -1t13 22l6 34q2 10 -2.5 22t-13.5 19q-5 4 -14 12t-29.5 40.5t-32.5 73.5q-26 89 6 271q2 11 -6 11q-8 1 -15 -10z" />
<glyph unicode="&#xe065;" d="M1000 1013l108 115q2 1 5 2t13 2t20.5 -1t25 -9.5t28.5 -21.5q22 -22 27 -43t0 -32l-6 -10l-108 -115zM350 1100h400q50 0 105 -13l-187 -187h-368q-41 0 -70.5 -29.5t-29.5 -70.5v-500q0 -41 29.5 -70.5t70.5 -29.5h500q41 0 70.5 29.5t29.5 70.5v182l200 200v-332 q0 -165 -93.5 -257.5t-256.5 -92.5h-400q-165 0 -257.5 92.5t-92.5 257.5v400q0 165 92.5 257.5t257.5 92.5zM1009 803l-362 -362l-161 -50l55 170l355 355z" />
<glyph unicode="&#xe066;" d="M350 1100h361q-164 -146 -216 -200h-195q-41 0 -70.5 -29.5t-29.5 -70.5v-500q0 -41 29.5 -70.5t70.5 -29.5h500q41 0 70.5 29.5t29.5 70.5l200 153v-103q0 -165 -92.5 -257.5t-257.5 -92.5h-400q-165 0 -257.5 92.5t-92.5 257.5v400q0 165 92.5 257.5t257.5 92.5z M824 1073l339 -301q8 -7 8 -17.5t-8 -17.5l-340 -306q-7 -6 -12.5 -4t-6.5 11v203q-26 1 -54.5 0t-78.5 -7.5t-92 -17.5t-86 -35t-70 -57q10 59 33 108t51.5 81.5t65 58.5t68.5 40.5t67 24.5t56 13.5t40 4.5v210q1 10 6.5 12.5t13.5 -4.5z" />
<glyph unicode="&#xe067;" d="M350 1100h350q60 0 127 -23l-178 -177h-349q-41 0 -70.5 -29.5t-29.5 -70.5v-500q0 -41 29.5 -70.5t70.5 -29.5h500q41 0 70.5 29.5t29.5 70.5v69l200 200v-219q0 -165 -92.5 -257.5t-257.5 -92.5h-400q-165 0 -257.5 92.5t-92.5 257.5v400q0 165 92.5 257.5t257.5 92.5z M643 639l395 395q7 7 17.5 7t17.5 -7l101 -101q7 -7 7 -17.5t-7 -17.5l-531 -532q-7 -7 -17.5 -7t-17.5 7l-248 248q-7 7 -7 17.5t7 17.5l101 101q7 7 17.5 7t17.5 -7l111 -111q8 -7 18 -7t18 7z" />
<glyph unicode="&#xe068;" d="M318 918l264 264q8 8 18 8t18 -8l260 -264q7 -8 4.5 -13t-12.5 -5h-170v-200h200v173q0 10 5 12t13 -5l264 -260q8 -7 8 -17.5t-8 -17.5l-264 -265q-8 -7 -13 -5t-5 12v173h-200v-200h170q10 0 12.5 -5t-4.5 -13l-260 -264q-8 -8 -18 -8t-18 8l-264 264q-8 8 -5.5 13 t12.5 5h175v200h-200v-173q0 -10 -5 -12t-13 5l-264 265q-8 7 -8 17.5t8 17.5l264 260q8 7 13 5t5 -12v-173h200v200h-175q-10 0 -12.5 5t5.5 13z" />
<glyph unicode="&#xe069;" d="M250 1100h100q21 0 35.5 -14.5t14.5 -35.5v-438l464 453q15 14 25.5 10t10.5 -25v-1000q0 -21 -10.5 -25t-25.5 10l-464 453v-438q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v1000q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe070;" d="M50 1100h100q21 0 35.5 -14.5t14.5 -35.5v-438l464 453q15 14 25.5 10t10.5 -25v-438l464 453q15 14 25.5 10t10.5 -25v-1000q0 -21 -10.5 -25t-25.5 10l-464 453v-438q0 -21 -10.5 -25t-25.5 10l-464 453v-438q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5 t-14.5 35.5v1000q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe071;" d="M1200 1050v-1000q0 -21 -10.5 -25t-25.5 10l-464 453v-438q0 -21 -10.5 -25t-25.5 10l-492 480q-15 14 -15 35t15 35l492 480q15 14 25.5 10t10.5 -25v-438l464 453q15 14 25.5 10t10.5 -25z" />
<glyph unicode="&#xe072;" d="M243 1074l814 -498q18 -11 18 -26t-18 -26l-814 -498q-18 -11 -30.5 -4t-12.5 28v1000q0 21 12.5 28t30.5 -4z" />
<glyph unicode="&#xe073;" d="M250 1000h200q21 0 35.5 -14.5t14.5 -35.5v-800q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v800q0 21 14.5 35.5t35.5 14.5zM650 1000h200q21 0 35.5 -14.5t14.5 -35.5v-800q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v800 q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe074;" d="M1100 950v-800q0 -21 -14.5 -35.5t-35.5 -14.5h-800q-21 0 -35.5 14.5t-14.5 35.5v800q0 21 14.5 35.5t35.5 14.5h800q21 0 35.5 -14.5t14.5 -35.5z" />
<glyph unicode="&#xe075;" d="M500 612v438q0 21 10.5 25t25.5 -10l492 -480q15 -14 15 -35t-15 -35l-492 -480q-15 -14 -25.5 -10t-10.5 25v438l-464 -453q-15 -14 -25.5 -10t-10.5 25v1000q0 21 10.5 25t25.5 -10z" />
<glyph unicode="&#xe076;" d="M1048 1102l100 1q20 0 35 -14.5t15 -35.5l5 -1000q0 -21 -14.5 -35.5t-35.5 -14.5l-100 -1q-21 0 -35.5 14.5t-14.5 35.5l-2 437l-463 -454q-14 -15 -24.5 -10.5t-10.5 25.5l-2 437l-462 -455q-15 -14 -25.5 -9.5t-10.5 24.5l-5 1000q0 21 10.5 25.5t25.5 -10.5l466 -450 l-2 438q0 20 10.5 24.5t25.5 -9.5l466 -451l-2 438q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe077;" d="M850 1100h100q21 0 35.5 -14.5t14.5 -35.5v-1000q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v438l-464 -453q-15 -14 -25.5 -10t-10.5 25v1000q0 21 10.5 25t25.5 -10l464 -453v438q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe078;" d="M686 1081l501 -540q15 -15 10.5 -26t-26.5 -11h-1042q-22 0 -26.5 11t10.5 26l501 540q15 15 36 15t36 -15zM150 400h1000q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1000q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe079;" d="M885 900l-352 -353l352 -353l-197 -198l-552 552l552 550z" />
<glyph unicode="&#xe080;" d="M1064 547l-551 -551l-198 198l353 353l-353 353l198 198z" />
<glyph unicode="&#xe081;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM650 900h-100q-21 0 -35.5 -14.5t-14.5 -35.5v-150h-150 q-21 0 -35.5 -14.5t-14.5 -35.5v-100q0 -21 14.5 -35.5t35.5 -14.5h150v-150q0 -21 14.5 -35.5t35.5 -14.5h100q21 0 35.5 14.5t14.5 35.5v150h150q21 0 35.5 14.5t14.5 35.5v100q0 21 -14.5 35.5t-35.5 14.5h-150v150q0 21 -14.5 35.5t-35.5 14.5z" />
<glyph unicode="&#xe082;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM850 700h-500q-21 0 -35.5 -14.5t-14.5 -35.5v-100q0 -21 14.5 -35.5 t35.5 -14.5h500q21 0 35.5 14.5t14.5 35.5v100q0 21 -14.5 35.5t-35.5 14.5z" />
<glyph unicode="&#xe083;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM741.5 913q-12.5 0 -21.5 -9l-120 -120l-120 120q-9 9 -21.5 9 t-21.5 -9l-141 -141q-9 -9 -9 -21.5t9 -21.5l120 -120l-120 -120q-9 -9 -9 -21.5t9 -21.5l141 -141q9 -9 21.5 -9t21.5 9l120 120l120 -120q9 -9 21.5 -9t21.5 9l141 141q9 9 9 21.5t-9 21.5l-120 120l120 120q9 9 9 21.5t-9 21.5l-141 141q-9 9 -21.5 9z" />
<glyph unicode="&#xe084;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM546 623l-84 85q-7 7 -17.5 7t-18.5 -7l-139 -139q-7 -8 -7 -18t7 -18 l242 -241q7 -8 17.5 -8t17.5 8l375 375q7 7 7 17.5t-7 18.5l-139 139q-7 7 -17.5 7t-17.5 -7z" />
<glyph unicode="&#xe085;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM588 941q-29 0 -59 -5.5t-63 -20.5t-58 -38.5t-41.5 -63t-16.5 -89.5 q0 -25 20 -25h131q30 -5 35 11q6 20 20.5 28t45.5 8q20 0 31.5 -10.5t11.5 -28.5q0 -23 -7 -34t-26 -18q-1 0 -13.5 -4t-19.5 -7.5t-20 -10.5t-22 -17t-18.5 -24t-15.5 -35t-8 -46q-1 -8 5.5 -16.5t20.5 -8.5h173q7 0 22 8t35 28t37.5 48t29.5 74t12 100q0 47 -17 83 t-42.5 57t-59.5 34.5t-64 18t-59 4.5zM675 400h-150q-10 0 -17.5 -7.5t-7.5 -17.5v-150q0 -10 7.5 -17.5t17.5 -7.5h150q10 0 17.5 7.5t7.5 17.5v150q0 10 -7.5 17.5t-17.5 7.5z" />
<glyph unicode="&#xe086;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM675 1000h-150q-10 0 -17.5 -7.5t-7.5 -17.5v-150q0 -10 7.5 -17.5 t17.5 -7.5h150q10 0 17.5 7.5t7.5 17.5v150q0 10 -7.5 17.5t-17.5 7.5zM675 700h-250q-10 0 -17.5 -7.5t-7.5 -17.5v-50q0 -10 7.5 -17.5t17.5 -7.5h75v-200h-75q-10 0 -17.5 -7.5t-7.5 -17.5v-50q0 -10 7.5 -17.5t17.5 -7.5h350q10 0 17.5 7.5t7.5 17.5v50q0 10 -7.5 17.5 t-17.5 7.5h-75v275q0 10 -7.5 17.5t-17.5 7.5z" />
<glyph unicode="&#xe087;" d="M525 1200h150q10 0 17.5 -7.5t7.5 -17.5v-194q103 -27 178.5 -102.5t102.5 -178.5h194q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-194q-27 -103 -102.5 -178.5t-178.5 -102.5v-194q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v194 q-103 27 -178.5 102.5t-102.5 178.5h-194q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5h194q27 103 102.5 178.5t178.5 102.5v194q0 10 7.5 17.5t17.5 7.5zM700 893v-168q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v168q-68 -23 -119 -74 t-74 -119h168q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-168q23 -68 74 -119t119 -74v168q0 10 7.5 17.5t17.5 7.5h150q10 0 17.5 -7.5t7.5 -17.5v-168q68 23 119 74t74 119h-168q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5h168 q-23 68 -74 119t-119 74z" />
<glyph unicode="&#xe088;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM600 1027q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5t57 -214.5 t155.5 -155.5t214.5 -57t214.5 57t155.5 155.5t57 214.5t-57 214.5t-155.5 155.5t-214.5 57zM759 823l64 -64q7 -7 7 -17.5t-7 -17.5l-124 -124l124 -124q7 -7 7 -17.5t-7 -17.5l-64 -64q-7 -7 -17.5 -7t-17.5 7l-124 124l-124 -124q-7 -7 -17.5 -7t-17.5 7l-64 64 q-7 7 -7 17.5t7 17.5l124 124l-124 124q-7 7 -7 17.5t7 17.5l64 64q7 7 17.5 7t17.5 -7l124 -124l124 124q7 7 17.5 7t17.5 -7z" />
<glyph unicode="&#xe089;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM600 1027q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5t57 -214.5 t155.5 -155.5t214.5 -57t214.5 57t155.5 155.5t57 214.5t-57 214.5t-155.5 155.5t-214.5 57zM782 788l106 -106q7 -7 7 -17.5t-7 -17.5l-320 -321q-8 -7 -18 -7t-18 7l-202 203q-8 7 -8 17.5t8 17.5l106 106q7 8 17.5 8t17.5 -8l79 -79l197 197q7 7 17.5 7t17.5 -7z" />
<glyph unicode="&#xe090;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM600 1027q-116 0 -214.5 -57t-155.5 -155.5t-57 -214.5q0 -120 65 -225 l587 587q-105 65 -225 65zM965 819l-584 -584q104 -62 219 -62q116 0 214.5 57t155.5 155.5t57 214.5q0 115 -62 219z" />
<glyph unicode="&#xe091;" d="M39 582l522 427q16 13 27.5 8t11.5 -26v-291h550q21 0 35.5 -14.5t14.5 -35.5v-200q0 -21 -14.5 -35.5t-35.5 -14.5h-550v-291q0 -21 -11.5 -26t-27.5 8l-522 427q-16 13 -16 32t16 32z" />
<glyph unicode="&#xe092;" d="M639 1009l522 -427q16 -13 16 -32t-16 -32l-522 -427q-16 -13 -27.5 -8t-11.5 26v291h-550q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5h550v291q0 21 11.5 26t27.5 -8z" />
<glyph unicode="&#xe093;" d="M682 1161l427 -522q13 -16 8 -27.5t-26 -11.5h-291v-550q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v550h-291q-21 0 -26 11.5t8 27.5l427 522q13 16 32 16t32 -16z" />
<glyph unicode="&#xe094;" d="M550 1200h200q21 0 35.5 -14.5t14.5 -35.5v-550h291q21 0 26 -11.5t-8 -27.5l-427 -522q-13 -16 -32 -16t-32 16l-427 522q-13 16 -8 27.5t26 11.5h291v550q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe095;" d="M639 1109l522 -427q16 -13 16 -32t-16 -32l-522 -427q-16 -13 -27.5 -8t-11.5 26v291q-94 -2 -182 -20t-170.5 -52t-147 -92.5t-100.5 -135.5q5 105 27 193.5t67.5 167t113 135t167 91.5t225.5 42v262q0 21 11.5 26t27.5 -8z" />
<glyph unicode="&#xe096;" d="M850 1200h300q21 0 35.5 -14.5t14.5 -35.5v-300q0 -21 -10.5 -25t-24.5 10l-94 94l-249 -249q-8 -7 -18 -7t-18 7l-106 106q-7 8 -7 18t7 18l249 249l-94 94q-14 14 -10 24.5t25 10.5zM350 0h-300q-21 0 -35.5 14.5t-14.5 35.5v300q0 21 10.5 25t24.5 -10l94 -94l249 249 q8 7 18 7t18 -7l106 -106q7 -8 7 -18t-7 -18l-249 -249l94 -94q14 -14 10 -24.5t-25 -10.5z" />
<glyph unicode="&#xe097;" d="M1014 1120l106 -106q7 -8 7 -18t-7 -18l-249 -249l94 -94q14 -14 10 -24.5t-25 -10.5h-300q-21 0 -35.5 14.5t-14.5 35.5v300q0 21 10.5 25t24.5 -10l94 -94l249 249q8 7 18 7t18 -7zM250 600h300q21 0 35.5 -14.5t14.5 -35.5v-300q0 -21 -10.5 -25t-24.5 10l-94 94 l-249 -249q-8 -7 -18 -7t-18 7l-106 106q-7 8 -7 18t7 18l249 249l-94 94q-14 14 -10 24.5t25 10.5z" />
<glyph unicode="&#xe101;" d="M600 1177q117 0 224 -45.5t184.5 -123t123 -184.5t45.5 -224t-45.5 -224t-123 -184.5t-184.5 -123t-224 -45.5t-224 45.5t-184.5 123t-123 184.5t-45.5 224t45.5 224t123 184.5t184.5 123t224 45.5zM704 900h-208q-20 0 -32 -14.5t-8 -34.5l58 -302q4 -20 21.5 -34.5 t37.5 -14.5h54q20 0 37.5 14.5t21.5 34.5l58 302q4 20 -8 34.5t-32 14.5zM675 400h-150q-10 0 -17.5 -7.5t-7.5 -17.5v-150q0 -10 7.5 -17.5t17.5 -7.5h150q10 0 17.5 7.5t7.5 17.5v150q0 10 -7.5 17.5t-17.5 7.5z" />
<glyph unicode="&#xe102;" d="M260 1200q9 0 19 -2t15 -4l5 -2q22 -10 44 -23l196 -118q21 -13 36 -24q29 -21 37 -12q11 13 49 35l196 118q22 13 45 23q17 7 38 7q23 0 47 -16.5t37 -33.5l13 -16q14 -21 18 -45l25 -123l8 -44q1 -9 8.5 -14.5t17.5 -5.5h61q10 0 17.5 -7.5t7.5 -17.5v-50 q0 -10 -7.5 -17.5t-17.5 -7.5h-50q-10 0 -17.5 -7.5t-7.5 -17.5v-175h-400v300h-200v-300h-400v175q0 10 -7.5 17.5t-17.5 7.5h-50q-10 0 -17.5 7.5t-7.5 17.5v50q0 10 7.5 17.5t17.5 7.5h61q11 0 18 3t7 8q0 4 9 52l25 128q5 25 19 45q2 3 5 7t13.5 15t21.5 19.5t26.5 15.5 t29.5 7zM915 1079l-166 -162q-7 -7 -5 -12t12 -5h219q10 0 15 7t2 17l-51 149q-3 10 -11 12t-15 -6zM463 917l-177 157q-8 7 -16 5t-11 -12l-51 -143q-3 -10 2 -17t15 -7h231q11 0 12.5 5t-5.5 12zM500 0h-375q-10 0 -17.5 7.5t-7.5 17.5v375h400v-400zM1100 400v-375 q0 -10 -7.5 -17.5t-17.5 -7.5h-375v400h400z" />
<glyph unicode="&#xe103;" d="M1165 1190q8 3 21 -6.5t13 -17.5q-2 -178 -24.5 -323.5t-55.5 -245.5t-87 -174.5t-102.5 -118.5t-118 -68.5t-118.5 -33t-120 -4.5t-105 9.5t-90 16.5q-61 12 -78 11q-4 1 -12.5 0t-34 -14.5t-52.5 -40.5l-153 -153q-26 -24 -37 -14.5t-11 43.5q0 64 42 102q8 8 50.5 45 t66.5 58q19 17 35 47t13 61q-9 55 -10 102.5t7 111t37 130t78 129.5q39 51 80 88t89.5 63.5t94.5 45t113.5 36t129 31t157.5 37t182 47.5zM1116 1098q-8 9 -22.5 -3t-45.5 -50q-38 -47 -119 -103.5t-142 -89.5l-62 -33q-56 -30 -102 -57t-104 -68t-102.5 -80.5t-85.5 -91 t-64 -104.5q-24 -56 -31 -86t2 -32t31.5 17.5t55.5 59.5q25 30 94 75.5t125.5 77.5t147.5 81q70 37 118.5 69t102 79.5t99 111t86.5 148.5q22 50 24 60t-6 19z" />
<glyph unicode="&#xe104;" d="M653 1231q-39 -67 -54.5 -131t-10.5 -114.5t24.5 -96.5t47.5 -80t63.5 -62.5t68.5 -46.5t65 -30q-4 7 -17.5 35t-18.5 39.5t-17 39.5t-17 43t-13 42t-9.5 44.5t-2 42t4 43t13.5 39t23 38.5q96 -42 165 -107.5t105 -138t52 -156t13 -159t-19 -149.5q-13 -55 -44 -106.5 t-68 -87t-78.5 -64.5t-72.5 -45t-53 -22q-72 -22 -127 -11q-31 6 -13 19q6 3 17 7q13 5 32.5 21t41 44t38.5 63.5t21.5 81.5t-6.5 94.5t-50 107t-104 115.5q10 -104 -0.5 -189t-37 -140.5t-65 -93t-84 -52t-93.5 -11t-95 24.5q-80 36 -131.5 114t-53.5 171q-2 23 0 49.5 t4.5 52.5t13.5 56t27.5 60t46 64.5t69.5 68.5q-8 -53 -5 -102.5t17.5 -90t34 -68.5t44.5 -39t49 -2q31 13 38.5 36t-4.5 55t-29 64.5t-36 75t-26 75.5q-15 85 2 161.5t53.5 128.5t85.5 92.5t93.5 61t81.5 25.5z" />
<glyph unicode="&#xe105;" d="M600 1094q82 0 160.5 -22.5t140 -59t116.5 -82.5t94.5 -95t68 -95t42.5 -82.5t14 -57.5t-14 -57.5t-43 -82.5t-68.5 -95t-94.5 -95t-116.5 -82.5t-140 -59t-159.5 -22.5t-159.5 22.5t-140 59t-116.5 82.5t-94.5 95t-68.5 95t-43 82.5t-14 57.5t14 57.5t42.5 82.5t68 95 t94.5 95t116.5 82.5t140 59t160.5 22.5zM888 829q-15 15 -18 12t5 -22q25 -57 25 -119q0 -124 -88 -212t-212 -88t-212 88t-88 212q0 59 23 114q8 19 4.5 22t-17.5 -12q-70 -69 -160 -184q-13 -16 -15 -40.5t9 -42.5q22 -36 47 -71t70 -82t92.5 -81t113 -58.5t133.5 -24.5 t133.5 24t113 58.5t92.5 81.5t70 81.5t47 70.5q11 18 9 42.5t-14 41.5q-90 117 -163 189zM448 727l-35 -36q-15 -15 -19.5 -38.5t4.5 -41.5q37 -68 93 -116q16 -13 38.5 -11t36.5 17l35 34q14 15 12.5 33.5t-16.5 33.5q-44 44 -89 117q-11 18 -28 20t-32 -12z" />
<glyph unicode="&#xe106;" d="M592 0h-148l31 120q-91 20 -175.5 68.5t-143.5 106.5t-103.5 119t-66.5 110t-22 76q0 21 14 57.5t42.5 82.5t68 95t94.5 95t116.5 82.5t140 59t160.5 22.5q61 0 126 -15l32 121h148zM944 770l47 181q108 -85 176.5 -192t68.5 -159q0 -26 -19.5 -71t-59.5 -102t-93 -112 t-129 -104.5t-158 -75.5l46 173q77 49 136 117t97 131q11 18 9 42.5t-14 41.5q-54 70 -107 130zM310 824q-70 -69 -160 -184q-13 -16 -15 -40.5t9 -42.5q18 -30 39 -60t57 -70.5t74 -73t90 -61t105 -41.5l41 154q-107 18 -178.5 101.5t-71.5 193.5q0 59 23 114q8 19 4.5 22 t-17.5 -12zM448 727l-35 -36q-15 -15 -19.5 -38.5t4.5 -41.5q37 -68 93 -116q16 -13 38.5 -11t36.5 17l12 11l22 86l-3 4q-44 44 -89 117q-11 18 -28 20t-32 -12z" />
<glyph unicode="&#xe107;" d="M-90 100l642 1066q20 31 48 28.5t48 -35.5l642 -1056q21 -32 7.5 -67.5t-50.5 -35.5h-1294q-37 0 -50.5 34t7.5 66zM155 200h345v75q0 10 7.5 17.5t17.5 7.5h150q10 0 17.5 -7.5t7.5 -17.5v-75h345l-445 723zM496 700h208q20 0 32 -14.5t8 -34.5l-58 -252 q-4 -20 -21.5 -34.5t-37.5 -14.5h-54q-20 0 -37.5 14.5t-21.5 34.5l-58 252q-4 20 8 34.5t32 14.5z" />
<glyph unicode="&#xe108;" d="M650 1200q62 0 106 -44t44 -106v-339l363 -325q15 -14 26 -38.5t11 -44.5v-41q0 -20 -12 -26.5t-29 5.5l-359 249v-263q100 -93 100 -113v-64q0 -21 -13 -29t-32 1l-205 128l-205 -128q-19 -9 -32 -1t-13 29v64q0 20 100 113v263l-359 -249q-17 -12 -29 -5.5t-12 26.5v41 q0 20 11 44.5t26 38.5l363 325v339q0 62 44 106t106 44z" />
<glyph unicode="&#xe109;" d="M850 1200h100q21 0 35.5 -14.5t14.5 -35.5v-50h50q21 0 35.5 -14.5t14.5 -35.5v-150h-1100v150q0 21 14.5 35.5t35.5 14.5h50v50q0 21 14.5 35.5t35.5 14.5h100q21 0 35.5 -14.5t14.5 -35.5v-50h500v50q0 21 14.5 35.5t35.5 14.5zM1100 800v-750q0 -21 -14.5 -35.5 t-35.5 -14.5h-1000q-21 0 -35.5 14.5t-14.5 35.5v750h1100zM100 600v-100h100v100h-100zM300 600v-100h100v100h-100zM500 600v-100h100v100h-100zM700 600v-100h100v100h-100zM900 600v-100h100v100h-100zM100 400v-100h100v100h-100zM300 400v-100h100v100h-100zM500 400 v-100h100v100h-100zM700 400v-100h100v100h-100zM900 400v-100h100v100h-100zM100 200v-100h100v100h-100zM300 200v-100h100v100h-100zM500 200v-100h100v100h-100zM700 200v-100h100v100h-100zM900 200v-100h100v100h-100z" />
<glyph unicode="&#xe110;" d="M1135 1165l249 -230q15 -14 15 -35t-15 -35l-249 -230q-14 -14 -24.5 -10t-10.5 25v150h-159l-600 -600h-291q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5h209l600 600h241v150q0 21 10.5 25t24.5 -10zM522 819l-141 -141l-122 122h-209q-21 0 -35.5 14.5 t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5h291zM1135 565l249 -230q15 -14 15 -35t-15 -35l-249 -230q-14 -14 -24.5 -10t-10.5 25v150h-241l-181 181l141 141l122 -122h159v150q0 21 10.5 25t24.5 -10z" />
<glyph unicode="&#xe111;" d="M100 1100h1000q41 0 70.5 -29.5t29.5 -70.5v-600q0 -41 -29.5 -70.5t-70.5 -29.5h-596l-304 -300v300h-100q-41 0 -70.5 29.5t-29.5 70.5v600q0 41 29.5 70.5t70.5 29.5z" />
<glyph unicode="&#xe112;" d="M150 1200h200q21 0 35.5 -14.5t14.5 -35.5v-250h-300v250q0 21 14.5 35.5t35.5 14.5zM850 1200h200q21 0 35.5 -14.5t14.5 -35.5v-250h-300v250q0 21 14.5 35.5t35.5 14.5zM1100 800v-300q0 -41 -3 -77.5t-15 -89.5t-32 -96t-58 -89t-89 -77t-129 -51t-174 -20t-174 20 t-129 51t-89 77t-58 89t-32 96t-15 89.5t-3 77.5v300h300v-250v-27v-42.5t1.5 -41t5 -38t10 -35t16.5 -30t25.5 -24.5t35 -19t46.5 -12t60 -4t60 4.5t46.5 12.5t35 19.5t25 25.5t17 30.5t10 35t5 38t2 40.5t-0.5 42v25v250h300z" />
<glyph unicode="&#xe113;" d="M1100 411l-198 -199l-353 353l-353 -353l-197 199l551 551z" />
<glyph unicode="&#xe114;" d="M1101 789l-550 -551l-551 551l198 199l353 -353l353 353z" />
<glyph unicode="&#xe115;" d="M404 1000h746q21 0 35.5 -14.5t14.5 -35.5v-551h150q21 0 25 -10.5t-10 -24.5l-230 -249q-14 -15 -35 -15t-35 15l-230 249q-14 14 -10 24.5t25 10.5h150v401h-381zM135 984l230 -249q14 -14 10 -24.5t-25 -10.5h-150v-400h385l215 -200h-750q-21 0 -35.5 14.5 t-14.5 35.5v550h-150q-21 0 -25 10.5t10 24.5l230 249q14 15 35 15t35 -15z" />
<glyph unicode="&#xe116;" d="M56 1200h94q17 0 31 -11t18 -27l38 -162h896q24 0 39 -18.5t10 -42.5l-100 -475q-5 -21 -27 -42.5t-55 -21.5h-633l48 -200h535q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-50v-50q0 -21 -14.5 -35.5t-35.5 -14.5t-35.5 14.5t-14.5 35.5v50h-300v-50 q0 -21 -14.5 -35.5t-35.5 -14.5t-35.5 14.5t-14.5 35.5v50h-31q-18 0 -32.5 10t-20.5 19l-5 10l-201 961h-54q-20 0 -35 14.5t-15 35.5t15 35.5t35 14.5z" />
<glyph unicode="&#xe117;" d="M1200 1000v-100h-1200v100h200q0 41 29.5 70.5t70.5 29.5h300q41 0 70.5 -29.5t29.5 -70.5h500zM0 800h1200v-800h-1200v800z" />
<glyph unicode="&#xe118;" d="M200 800l-200 -400v600h200q0 41 29.5 70.5t70.5 29.5h300q42 0 71 -29.5t29 -70.5h500v-200h-1000zM1500 700l-300 -700h-1200l300 700h1200z" />
<glyph unicode="&#xe119;" d="M635 1184l230 -249q14 -14 10 -24.5t-25 -10.5h-150v-601h150q21 0 25 -10.5t-10 -24.5l-230 -249q-14 -15 -35 -15t-35 15l-230 249q-14 14 -10 24.5t25 10.5h150v601h-150q-21 0 -25 10.5t10 24.5l230 249q14 15 35 15t35 -15z" />
<glyph unicode="&#xe120;" d="M936 864l249 -229q14 -15 14 -35.5t-14 -35.5l-249 -229q-15 -15 -25.5 -10.5t-10.5 24.5v151h-600v-151q0 -20 -10.5 -24.5t-25.5 10.5l-249 229q-14 15 -14 35.5t14 35.5l249 229q15 15 25.5 10.5t10.5 -25.5v-149h600v149q0 21 10.5 25.5t25.5 -10.5z" />
<glyph unicode="&#xe121;" d="M1169 400l-172 732q-5 23 -23 45.5t-38 22.5h-672q-20 0 -38 -20t-23 -41l-172 -739h1138zM1100 300h-1000q-41 0 -70.5 -29.5t-29.5 -70.5v-100q0 -41 29.5 -70.5t70.5 -29.5h1000q41 0 70.5 29.5t29.5 70.5v100q0 41 -29.5 70.5t-70.5 29.5zM800 100v100h100v-100h-100 zM1000 100v100h100v-100h-100z" />
<glyph unicode="&#xe122;" d="M1150 1100q21 0 35.5 -14.5t14.5 -35.5v-850q0 -21 -14.5 -35.5t-35.5 -14.5t-35.5 14.5t-14.5 35.5v850q0 21 14.5 35.5t35.5 14.5zM1000 200l-675 200h-38l47 -276q3 -16 -5.5 -20t-29.5 -4h-7h-84q-20 0 -34.5 14t-18.5 35q-55 337 -55 351v250v6q0 16 1 23.5t6.5 14 t17.5 6.5h200l675 250v-850zM0 750v-250q-4 0 -11 0.5t-24 6t-30 15t-24 30t-11 48.5v50q0 26 10.5 46t25 30t29 16t25.5 7z" />
<glyph unicode="&#xe123;" d="M553 1200h94q20 0 29 -10.5t3 -29.5l-18 -37q83 -19 144 -82.5t76 -140.5l63 -327l118 -173h17q19 0 33 -14.5t14 -35t-13 -40.5t-31 -27q-8 -4 -23 -9.5t-65 -19.5t-103 -25t-132.5 -20t-158.5 -9q-57 0 -115 5t-104 12t-88.5 15.5t-73.5 17.5t-54.5 16t-35.5 12l-11 4 q-18 8 -31 28t-13 40.5t14 35t33 14.5h17l118 173l63 327q15 77 76 140t144 83l-18 32q-6 19 3.5 32t28.5 13zM498 110q50 -6 102 -6q53 0 102 6q-12 -49 -39.5 -79.5t-62.5 -30.5t-63 30.5t-39 79.5z" />
<glyph unicode="&#xe124;" d="M800 946l224 78l-78 -224l234 -45l-180 -155l180 -155l-234 -45l78 -224l-224 78l-45 -234l-155 180l-155 -180l-45 234l-224 -78l78 224l-234 45l180 155l-180 155l234 45l-78 224l224 -78l45 234l155 -180l155 180z" />
<glyph unicode="&#xe125;" d="M650 1200h50q40 0 70 -40.5t30 -84.5v-150l-28 -125h328q40 0 70 -40.5t30 -84.5v-100q0 -45 -29 -74l-238 -344q-16 -24 -38 -40.5t-45 -16.5h-250q-7 0 -42 25t-66 50l-31 25h-61q-45 0 -72.5 18t-27.5 57v400q0 36 20 63l145 196l96 198q13 28 37.5 48t51.5 20z M650 1100l-100 -212l-150 -213v-375h100l136 -100h214l250 375v125h-450l50 225v175h-50zM50 800h100q21 0 35.5 -14.5t14.5 -35.5v-500q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v500q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe126;" d="M600 1100h250q23 0 45 -16.5t38 -40.5l238 -344q29 -29 29 -74v-100q0 -44 -30 -84.5t-70 -40.5h-328q28 -118 28 -125v-150q0 -44 -30 -84.5t-70 -40.5h-50q-27 0 -51.5 20t-37.5 48l-96 198l-145 196q-20 27 -20 63v400q0 39 27.5 57t72.5 18h61q124 100 139 100z M50 1000h100q21 0 35.5 -14.5t14.5 -35.5v-500q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v500q0 21 14.5 35.5t35.5 14.5zM636 1000l-136 -100h-100v-375l150 -213l100 -212h50v175l-50 225h450v125l-250 375h-214z" />
<glyph unicode="&#xe127;" d="M356 873l363 230q31 16 53 -6l110 -112q13 -13 13.5 -32t-11.5 -34l-84 -121h302q84 0 138 -38t54 -110t-55 -111t-139 -39h-106l-131 -339q-6 -21 -19.5 -41t-28.5 -20h-342q-7 0 -90 81t-83 94v525q0 17 14 35.5t28 28.5zM400 792v-503l100 -89h293l131 339 q6 21 19.5 41t28.5 20h203q21 0 30.5 25t0.5 50t-31 25h-456h-7h-6h-5.5t-6 0.5t-5 1.5t-5 2t-4 2.5t-4 4t-2.5 4.5q-12 25 5 47l146 183l-86 83zM50 800h100q21 0 35.5 -14.5t14.5 -35.5v-500q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v500 q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe128;" d="M475 1103l366 -230q2 -1 6 -3.5t14 -10.5t18 -16.5t14.5 -20t6.5 -22.5v-525q0 -13 -86 -94t-93 -81h-342q-15 0 -28.5 20t-19.5 41l-131 339h-106q-85 0 -139.5 39t-54.5 111t54 110t138 38h302l-85 121q-11 15 -10.5 34t13.5 32l110 112q22 22 53 6zM370 945l146 -183 q17 -22 5 -47q-2 -2 -3.5 -4.5t-4 -4t-4 -2.5t-5 -2t-5 -1.5t-6 -0.5h-6h-6.5h-6h-475v-100h221q15 0 29 -20t20 -41l130 -339h294l106 89v503l-342 236zM1050 800h100q21 0 35.5 -14.5t14.5 -35.5v-500q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5 v500q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe129;" d="M550 1294q72 0 111 -55t39 -139v-106l339 -131q21 -6 41 -19.5t20 -28.5v-342q0 -7 -81 -90t-94 -83h-525q-17 0 -35.5 14t-28.5 28l-9 14l-230 363q-16 31 6 53l112 110q13 13 32 13.5t34 -11.5l121 -84v302q0 84 38 138t110 54zM600 972v203q0 21 -25 30.5t-50 0.5 t-25 -31v-456v-7v-6v-5.5t-0.5 -6t-1.5 -5t-2 -5t-2.5 -4t-4 -4t-4.5 -2.5q-25 -12 -47 5l-183 146l-83 -86l236 -339h503l89 100v293l-339 131q-21 6 -41 19.5t-20 28.5zM450 200h500q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-500 q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe130;" d="M350 1100h500q21 0 35.5 14.5t14.5 35.5v100q0 21 -14.5 35.5t-35.5 14.5h-500q-21 0 -35.5 -14.5t-14.5 -35.5v-100q0 -21 14.5 -35.5t35.5 -14.5zM600 306v-106q0 -84 -39 -139t-111 -55t-110 54t-38 138v302l-121 -84q-15 -12 -34 -11.5t-32 13.5l-112 110 q-22 22 -6 53l230 363q1 2 3.5 6t10.5 13.5t16.5 17t20 13.5t22.5 6h525q13 0 94 -83t81 -90v-342q0 -15 -20 -28.5t-41 -19.5zM308 900l-236 -339l83 -86l183 146q22 17 47 5q2 -1 4.5 -2.5t4 -4t2.5 -4t2 -5t1.5 -5t0.5 -6v-5.5v-6v-7v-456q0 -22 25 -31t50 0.5t25 30.5 v203q0 15 20 28.5t41 19.5l339 131v293l-89 100h-503z" />
<glyph unicode="&#xe131;" d="M600 1178q118 0 225 -45.5t184.5 -123t123 -184.5t45.5 -225t-45.5 -225t-123 -184.5t-184.5 -123t-225 -45.5t-225 45.5t-184.5 123t-123 184.5t-45.5 225t45.5 225t123 184.5t184.5 123t225 45.5zM914 632l-275 223q-16 13 -27.5 8t-11.5 -26v-137h-275 q-10 0 -17.5 -7.5t-7.5 -17.5v-150q0 -10 7.5 -17.5t17.5 -7.5h275v-137q0 -21 11.5 -26t27.5 8l275 223q16 13 16 32t-16 32z" />
<glyph unicode="&#xe132;" d="M600 1178q118 0 225 -45.5t184.5 -123t123 -184.5t45.5 -225t-45.5 -225t-123 -184.5t-184.5 -123t-225 -45.5t-225 45.5t-184.5 123t-123 184.5t-45.5 225t45.5 225t123 184.5t184.5 123t225 45.5zM561 855l-275 -223q-16 -13 -16 -32t16 -32l275 -223q16 -13 27.5 -8 t11.5 26v137h275q10 0 17.5 7.5t7.5 17.5v150q0 10 -7.5 17.5t-17.5 7.5h-275v137q0 21 -11.5 26t-27.5 -8z" />
<glyph unicode="&#xe133;" d="M600 1178q118 0 225 -45.5t184.5 -123t123 -184.5t45.5 -225t-45.5 -225t-123 -184.5t-184.5 -123t-225 -45.5t-225 45.5t-184.5 123t-123 184.5t-45.5 225t45.5 225t123 184.5t184.5 123t225 45.5zM855 639l-223 275q-13 16 -32 16t-32 -16l-223 -275q-13 -16 -8 -27.5 t26 -11.5h137v-275q0 -10 7.5 -17.5t17.5 -7.5h150q10 0 17.5 7.5t7.5 17.5v275h137q21 0 26 11.5t-8 27.5z" />
<glyph unicode="&#xe134;" d="M600 1178q118 0 225 -45.5t184.5 -123t123 -184.5t45.5 -225t-45.5 -225t-123 -184.5t-184.5 -123t-225 -45.5t-225 45.5t-184.5 123t-123 184.5t-45.5 225t45.5 225t123 184.5t184.5 123t225 45.5zM675 900h-150q-10 0 -17.5 -7.5t-7.5 -17.5v-275h-137q-21 0 -26 -11.5 t8 -27.5l223 -275q13 -16 32 -16t32 16l223 275q13 16 8 27.5t-26 11.5h-137v275q0 10 -7.5 17.5t-17.5 7.5z" />
<glyph unicode="&#xe135;" d="M600 1176q116 0 222.5 -46t184 -123.5t123.5 -184t46 -222.5t-46 -222.5t-123.5 -184t-184 -123.5t-222.5 -46t-222.5 46t-184 123.5t-123.5 184t-46 222.5t46 222.5t123.5 184t184 123.5t222.5 46zM627 1101q-15 -12 -36.5 -20.5t-35.5 -12t-43 -8t-39 -6.5 q-15 -3 -45.5 0t-45.5 -2q-20 -7 -51.5 -26.5t-34.5 -34.5q-3 -11 6.5 -22.5t8.5 -18.5q-3 -34 -27.5 -91t-29.5 -79q-9 -34 5 -93t8 -87q0 -9 17 -44.5t16 -59.5q12 0 23 -5t23.5 -15t19.5 -14q16 -8 33 -15t40.5 -15t34.5 -12q21 -9 52.5 -32t60 -38t57.5 -11 q7 -15 -3 -34t-22.5 -40t-9.5 -38q13 -21 23 -34.5t27.5 -27.5t36.5 -18q0 -7 -3.5 -16t-3.5 -14t5 -17q104 -2 221 112q30 29 46.5 47t34.5 49t21 63q-13 8 -37 8.5t-36 7.5q-15 7 -49.5 15t-51.5 19q-18 0 -41 -0.5t-43 -1.5t-42 -6.5t-38 -16.5q-51 -35 -66 -12 q-4 1 -3.5 25.5t0.5 25.5q-6 13 -26.5 17.5t-24.5 6.5q1 15 -0.5 30.5t-7 28t-18.5 11.5t-31 -21q-23 -25 -42 4q-19 28 -8 58q6 16 22 22q6 -1 26 -1.5t33.5 -4t19.5 -13.5q7 -12 18 -24t21.5 -20.5t20 -15t15.5 -10.5l5 -3q2 12 7.5 30.5t8 34.5t-0.5 32q-3 18 3.5 29 t18 22.5t15.5 24.5q6 14 10.5 35t8 31t15.5 22.5t34 22.5q-6 18 10 36q8 0 24 -1.5t24.5 -1.5t20 4.5t20.5 15.5q-10 23 -31 42.5t-37.5 29.5t-49 27t-43.5 23q0 1 2 8t3 11.5t1.5 10.5t-1 9.5t-4.5 4.5q31 -13 58.5 -14.5t38.5 2.5l12 5q5 28 -9.5 46t-36.5 24t-50 15 t-41 20q-18 -4 -37 0zM613 994q0 -17 8 -42t17 -45t9 -23q-8 1 -39.5 5.5t-52.5 10t-37 16.5q3 11 16 29.5t16 25.5q10 -10 19 -10t14 6t13.5 14.5t16.5 12.5z" />
<glyph unicode="&#xe136;" d="M756 1157q164 92 306 -9l-259 -138l145 -232l251 126q6 -89 -34 -156.5t-117 -110.5q-60 -34 -127 -39.5t-126 16.5l-596 -596q-15 -16 -36.5 -16t-36.5 16l-111 110q-15 15 -15 36.5t15 37.5l600 599q-34 101 5.5 201.5t135.5 154.5z" />
<glyph unicode="&#xe137;" horiz-adv-x="1220" d="M100 1196h1000q41 0 70.5 -29.5t29.5 -70.5v-100q0 -41 -29.5 -70.5t-70.5 -29.5h-1000q-41 0 -70.5 29.5t-29.5 70.5v100q0 41 29.5 70.5t70.5 29.5zM1100 1096h-200v-100h200v100zM100 796h1000q41 0 70.5 -29.5t29.5 -70.5v-100q0 -41 -29.5 -70.5t-70.5 -29.5h-1000 q-41 0 -70.5 29.5t-29.5 70.5v100q0 41 29.5 70.5t70.5 29.5zM1100 696h-500v-100h500v100zM100 396h1000q41 0 70.5 -29.5t29.5 -70.5v-100q0 -41 -29.5 -70.5t-70.5 -29.5h-1000q-41 0 -70.5 29.5t-29.5 70.5v100q0 41 29.5 70.5t70.5 29.5zM1100 296h-300v-100h300v100z " />
<glyph unicode="&#xe138;" d="M150 1200h900q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-900q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5zM700 500v-300l-200 -200v500l-350 500h900z" />
<glyph unicode="&#xe139;" d="M500 1200h200q41 0 70.5 -29.5t29.5 -70.5v-100h300q41 0 70.5 -29.5t29.5 -70.5v-400h-500v100h-200v-100h-500v400q0 41 29.5 70.5t70.5 29.5h300v100q0 41 29.5 70.5t70.5 29.5zM500 1100v-100h200v100h-200zM1200 400v-200q0 -41 -29.5 -70.5t-70.5 -29.5h-1000 q-41 0 -70.5 29.5t-29.5 70.5v200h1200z" />
<glyph unicode="&#xe140;" d="M50 1200h300q21 0 25 -10.5t-10 -24.5l-94 -94l199 -199q7 -8 7 -18t-7 -18l-106 -106q-8 -7 -18 -7t-18 7l-199 199l-94 -94q-14 -14 -24.5 -10t-10.5 25v300q0 21 14.5 35.5t35.5 14.5zM850 1200h300q21 0 35.5 -14.5t14.5 -35.5v-300q0 -21 -10.5 -25t-24.5 10l-94 94 l-199 -199q-8 -7 -18 -7t-18 7l-106 106q-7 8 -7 18t7 18l199 199l-94 94q-14 14 -10 24.5t25 10.5zM364 470l106 -106q7 -8 7 -18t-7 -18l-199 -199l94 -94q14 -14 10 -24.5t-25 -10.5h-300q-21 0 -35.5 14.5t-14.5 35.5v300q0 21 10.5 25t24.5 -10l94 -94l199 199 q8 7 18 7t18 -7zM1071 271l94 94q14 14 24.5 10t10.5 -25v-300q0 -21 -14.5 -35.5t-35.5 -14.5h-300q-21 0 -25 10.5t10 24.5l94 94l-199 199q-7 8 -7 18t7 18l106 106q8 7 18 7t18 -7z" />
<glyph unicode="&#xe141;" d="M596 1192q121 0 231.5 -47.5t190 -127t127 -190t47.5 -231.5t-47.5 -231.5t-127 -190.5t-190 -127t-231.5 -47t-231.5 47t-190.5 127t-127 190.5t-47 231.5t47 231.5t127 190t190.5 127t231.5 47.5zM596 1010q-112 0 -207.5 -55.5t-151 -151t-55.5 -207.5t55.5 -207.5 t151 -151t207.5 -55.5t207.5 55.5t151 151t55.5 207.5t-55.5 207.5t-151 151t-207.5 55.5zM454.5 905q22.5 0 38.5 -16t16 -38.5t-16 -39t-38.5 -16.5t-38.5 16.5t-16 39t16 38.5t38.5 16zM754.5 905q22.5 0 38.5 -16t16 -38.5t-16 -39t-38 -16.5q-14 0 -29 10l-55 -145 q17 -23 17 -51q0 -36 -25.5 -61.5t-61.5 -25.5t-61.5 25.5t-25.5 61.5q0 32 20.5 56.5t51.5 29.5l122 126l1 1q-9 14 -9 28q0 23 16 39t38.5 16zM345.5 709q22.5 0 38.5 -16t16 -38.5t-16 -38.5t-38.5 -16t-38.5 16t-16 38.5t16 38.5t38.5 16zM854.5 709q22.5 0 38.5 -16 t16 -38.5t-16 -38.5t-38.5 -16t-38.5 16t-16 38.5t16 38.5t38.5 16z" />
<glyph unicode="&#xe142;" d="M546 173l469 470q91 91 99 192q7 98 -52 175.5t-154 94.5q-22 4 -47 4q-34 0 -66.5 -10t-56.5 -23t-55.5 -38t-48 -41.5t-48.5 -47.5q-376 -375 -391 -390q-30 -27 -45 -41.5t-37.5 -41t-32 -46.5t-16 -47.5t-1.5 -56.5q9 -62 53.5 -95t99.5 -33q74 0 125 51l548 548 q36 36 20 75q-7 16 -21.5 26t-32.5 10q-26 0 -50 -23q-13 -12 -39 -38l-341 -338q-15 -15 -35.5 -15.5t-34.5 13.5t-14 34.5t14 34.5q327 333 361 367q35 35 67.5 51.5t78.5 16.5q14 0 29 -1q44 -8 74.5 -35.5t43.5 -68.5q14 -47 2 -96.5t-47 -84.5q-12 -11 -32 -32 t-79.5 -81t-114.5 -115t-124.5 -123.5t-123 -119.5t-96.5 -89t-57 -45q-56 -27 -120 -27q-70 0 -129 32t-93 89q-48 78 -35 173t81 163l511 511q71 72 111 96q91 55 198 55q80 0 152 -33q78 -36 129.5 -103t66.5 -154q17 -93 -11 -183.5t-94 -156.5l-482 -476 q-15 -15 -36 -16t-37 14t-17.5 34t14.5 35z" />
<glyph unicode="&#xe143;" d="M649 949q48 68 109.5 104t121.5 38.5t118.5 -20t102.5 -64t71 -100.5t27 -123q0 -57 -33.5 -117.5t-94 -124.5t-126.5 -127.5t-150 -152.5t-146 -174q-62 85 -145.5 174t-150 152.5t-126.5 127.5t-93.5 124.5t-33.5 117.5q0 64 28 123t73 100.5t104 64t119 20 t120.5 -38.5t104.5 -104zM896 972q-33 0 -64.5 -19t-56.5 -46t-47.5 -53.5t-43.5 -45.5t-37.5 -19t-36 19t-40 45.5t-43 53.5t-54 46t-65.5 19q-67 0 -122.5 -55.5t-55.5 -132.5q0 -23 13.5 -51t46 -65t57.5 -63t76 -75l22 -22q15 -14 44 -44t50.5 -51t46 -44t41 -35t23 -12 t23.5 12t42.5 36t46 44t52.5 52t44 43q4 4 12 13q43 41 63.5 62t52 55t46 55t26 46t11.5 44q0 79 -53 133.5t-120 54.5z" />
<glyph unicode="&#xe144;" d="M776.5 1214q93.5 0 159.5 -66l141 -141q66 -66 66 -160q0 -42 -28 -95.5t-62 -87.5l-29 -29q-31 53 -77 99l-18 18l95 95l-247 248l-389 -389l212 -212l-105 -106l-19 18l-141 141q-66 66 -66 159t66 159l283 283q65 66 158.5 66zM600 706l105 105q10 -8 19 -17l141 -141 q66 -66 66 -159t-66 -159l-283 -283q-66 -66 -159 -66t-159 66l-141 141q-66 66 -66 159.5t66 159.5l55 55q29 -55 75 -102l18 -17l-95 -95l247 -248l389 389z" />
<glyph unicode="&#xe145;" d="M603 1200q85 0 162 -15t127 -38t79 -48t29 -46v-953q0 -41 -29.5 -70.5t-70.5 -29.5h-600q-41 0 -70.5 29.5t-29.5 70.5v953q0 21 30 46.5t81 48t129 37.5t163 15zM300 1000v-700h600v700h-600zM600 254q-43 0 -73.5 -30.5t-30.5 -73.5t30.5 -73.5t73.5 -30.5t73.5 30.5 t30.5 73.5t-30.5 73.5t-73.5 30.5z" />
<glyph unicode="&#xe146;" d="M902 1185l283 -282q15 -15 15 -36t-14.5 -35.5t-35.5 -14.5t-35 15l-36 35l-279 -267v-300l-212 210l-308 -307l-280 -203l203 280l307 308l-210 212h300l267 279l-35 36q-15 14 -15 35t14.5 35.5t35.5 14.5t35 -15z" />
<glyph unicode="&#xe148;" d="M700 1248v-78q38 -5 72.5 -14.5t75.5 -31.5t71 -53.5t52 -84t24 -118.5h-159q-4 36 -10.5 59t-21 45t-40 35.5t-64.5 20.5v-307l64 -13q34 -7 64 -16.5t70 -32t67.5 -52.5t47.5 -80t20 -112q0 -139 -89 -224t-244 -97v-77h-100v79q-150 16 -237 103q-40 40 -52.5 93.5 t-15.5 139.5h139q5 -77 48.5 -126t117.5 -65v335l-27 8q-46 14 -79 26.5t-72 36t-63 52t-40 72.5t-16 98q0 70 25 126t67.5 92t94.5 57t110 27v77h100zM600 754v274q-29 -4 -50 -11t-42 -21.5t-31.5 -41.5t-10.5 -65q0 -29 7 -50.5t16.5 -34t28.5 -22.5t31.5 -14t37.5 -10 q9 -3 13 -4zM700 547v-310q22 2 42.5 6.5t45 15.5t41.5 27t29 42t12 59.5t-12.5 59.5t-38 44.5t-53 31t-66.5 24.5z" />
<glyph unicode="&#xe149;" d="M561 1197q84 0 160.5 -40t123.5 -109.5t47 -147.5h-153q0 40 -19.5 71.5t-49.5 48.5t-59.5 26t-55.5 9q-37 0 -79 -14.5t-62 -35.5q-41 -44 -41 -101q0 -26 13.5 -63t26.5 -61t37 -66q6 -9 9 -14h241v-100h-197q8 -50 -2.5 -115t-31.5 -95q-45 -62 -99 -112 q34 10 83 17.5t71 7.5q32 1 102 -16t104 -17q83 0 136 30l50 -147q-31 -19 -58 -30.5t-55 -15.5t-42 -4.5t-46 -0.5q-23 0 -76 17t-111 32.5t-96 11.5q-39 -3 -82 -16t-67 -25l-23 -11l-55 145q4 3 16 11t15.5 10.5t13 9t15.5 12t14.5 14t17.5 18.5q48 55 54 126.5 t-30 142.5h-221v100h166q-23 47 -44 104q-7 20 -12 41.5t-6 55.5t6 66.5t29.5 70.5t58.5 71q97 88 263 88z" />
<glyph unicode="&#xe150;" d="M400 300h150q21 0 25 -11t-10 -25l-230 -250q-14 -15 -35 -15t-35 15l-230 250q-14 14 -10 25t25 11h150v900h200v-900zM935 1184l230 -249q14 -14 10 -24.5t-25 -10.5h-150v-900h-200v900h-150q-21 0 -25 10.5t10 24.5l230 249q14 15 35 15t35 -15z" />
<glyph unicode="&#xe151;" d="M1000 700h-100v100h-100v-100h-100v500h300v-500zM400 300h150q21 0 25 -11t-10 -25l-230 -250q-14 -15 -35 -15t-35 15l-230 250q-14 14 -10 25t25 11h150v900h200v-900zM801 1100v-200h100v200h-100zM1000 350l-200 -250h200v-100h-300v150l200 250h-200v100h300v-150z " />
<glyph unicode="&#xe152;" d="M400 300h150q21 0 25 -11t-10 -25l-230 -250q-14 -15 -35 -15t-35 15l-230 250q-14 14 -10 25t25 11h150v900h200v-900zM1000 1050l-200 -250h200v-100h-300v150l200 250h-200v100h300v-150zM1000 0h-100v100h-100v-100h-100v500h300v-500zM801 400v-200h100v200h-100z " />
<glyph unicode="&#xe153;" d="M400 300h150q21 0 25 -11t-10 -25l-230 -250q-14 -15 -35 -15t-35 15l-230 250q-14 14 -10 25t25 11h150v900h200v-900zM1000 700h-100v400h-100v100h200v-500zM1100 0h-100v100h-200v400h300v-500zM901 400v-200h100v200h-100z" />
<glyph unicode="&#xe154;" d="M400 300h150q21 0 25 -11t-10 -25l-230 -250q-14 -15 -35 -15t-35 15l-230 250q-14 14 -10 25t25 11h150v900h200v-900zM1100 700h-100v100h-200v400h300v-500zM901 1100v-200h100v200h-100zM1000 0h-100v400h-100v100h200v-500z" />
<glyph unicode="&#xe155;" d="M400 300h150q21 0 25 -11t-10 -25l-230 -250q-14 -15 -35 -15t-35 15l-230 250q-14 14 -10 25t25 11h150v900h200v-900zM900 1000h-200v200h200v-200zM1000 700h-300v200h300v-200zM1100 400h-400v200h400v-200zM1200 100h-500v200h500v-200z" />
<glyph unicode="&#xe156;" d="M400 300h150q21 0 25 -11t-10 -25l-230 -250q-14 -15 -35 -15t-35 15l-230 250q-14 14 -10 25t25 11h150v900h200v-900zM1200 1000h-500v200h500v-200zM1100 700h-400v200h400v-200zM1000 400h-300v200h300v-200zM900 100h-200v200h200v-200z" />
<glyph unicode="&#xe157;" d="M350 1100h400q162 0 256 -93.5t94 -256.5v-400q0 -165 -93.5 -257.5t-256.5 -92.5h-400q-165 0 -257.5 92.5t-92.5 257.5v400q0 165 92.5 257.5t257.5 92.5zM800 900h-500q-41 0 -70.5 -29.5t-29.5 -70.5v-500q0 -41 29.5 -70.5t70.5 -29.5h500q41 0 70.5 29.5t29.5 70.5 v500q0 41 -29.5 70.5t-70.5 29.5z" />
<glyph unicode="&#xe158;" d="M350 1100h400q165 0 257.5 -92.5t92.5 -257.5v-400q0 -165 -92.5 -257.5t-257.5 -92.5h-400q-163 0 -256.5 92.5t-93.5 257.5v400q0 163 94 256.5t256 93.5zM800 900h-500q-41 0 -70.5 -29.5t-29.5 -70.5v-500q0 -41 29.5 -70.5t70.5 -29.5h500q41 0 70.5 29.5t29.5 70.5 v500q0 41 -29.5 70.5t-70.5 29.5zM440 770l253 -190q17 -12 17 -30t-17 -30l-253 -190q-16 -12 -28 -6.5t-12 26.5v400q0 21 12 26.5t28 -6.5z" />
<glyph unicode="&#xe159;" d="M350 1100h400q163 0 256.5 -94t93.5 -256v-400q0 -165 -92.5 -257.5t-257.5 -92.5h-400q-165 0 -257.5 92.5t-92.5 257.5v400q0 163 92.5 256.5t257.5 93.5zM800 900h-500q-41 0 -70.5 -29.5t-29.5 -70.5v-500q0 -41 29.5 -70.5t70.5 -29.5h500q41 0 70.5 29.5t29.5 70.5 v500q0 41 -29.5 70.5t-70.5 29.5zM350 700h400q21 0 26.5 -12t-6.5 -28l-190 -253q-12 -17 -30 -17t-30 17l-190 253q-12 16 -6.5 28t26.5 12z" />
<glyph unicode="&#xe160;" d="M350 1100h400q165 0 257.5 -92.5t92.5 -257.5v-400q0 -163 -92.5 -256.5t-257.5 -93.5h-400q-163 0 -256.5 94t-93.5 256v400q0 165 92.5 257.5t257.5 92.5zM800 900h-500q-41 0 -70.5 -29.5t-29.5 -70.5v-500q0 -41 29.5 -70.5t70.5 -29.5h500q41 0 70.5 29.5t29.5 70.5 v500q0 41 -29.5 70.5t-70.5 29.5zM580 693l190 -253q12 -16 6.5 -28t-26.5 -12h-400q-21 0 -26.5 12t6.5 28l190 253q12 17 30 17t30 -17z" />
<glyph unicode="&#xe161;" d="M550 1100h400q165 0 257.5 -92.5t92.5 -257.5v-400q0 -165 -92.5 -257.5t-257.5 -92.5h-400q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5h450q41 0 70.5 29.5t29.5 70.5v500q0 41 -29.5 70.5t-70.5 29.5h-450q-21 0 -35.5 14.5t-14.5 35.5v100 q0 21 14.5 35.5t35.5 14.5zM338 867l324 -284q16 -14 16 -33t-16 -33l-324 -284q-16 -14 -27 -9t-11 26v150h-250q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5h250v150q0 21 11 26t27 -9z" />
<glyph unicode="&#xe162;" d="M793 1182l9 -9q8 -10 5 -27q-3 -11 -79 -225.5t-78 -221.5l300 1q24 0 32.5 -17.5t-5.5 -35.5q-1 0 -133.5 -155t-267 -312.5t-138.5 -162.5q-12 -15 -26 -15h-9l-9 8q-9 11 -4 32q2 9 42 123.5t79 224.5l39 110h-302q-23 0 -31 19q-10 21 6 41q75 86 209.5 237.5 t228 257t98.5 111.5q9 16 25 16h9z" />
<glyph unicode="&#xe163;" d="M350 1100h400q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-450q-41 0 -70.5 -29.5t-29.5 -70.5v-500q0 -41 29.5 -70.5t70.5 -29.5h450q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-165 0 -257.5 92.5t-92.5 257.5v400 q0 165 92.5 257.5t257.5 92.5zM938 867l324 -284q16 -14 16 -33t-16 -33l-324 -284q-16 -14 -27 -9t-11 26v150h-250q-21 0 -35.5 14.5t-14.5 35.5v200q0 21 14.5 35.5t35.5 14.5h250v150q0 21 11 26t27 -9z" />
<glyph unicode="&#xe164;" d="M750 1200h400q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -10.5 -25t-24.5 10l-109 109l-312 -312q-15 -15 -35.5 -15t-35.5 15l-141 141q-15 15 -15 35.5t15 35.5l312 312l-109 109q-14 14 -10 24.5t25 10.5zM456 900h-156q-41 0 -70.5 -29.5t-29.5 -70.5v-500 q0 -41 29.5 -70.5t70.5 -29.5h500q41 0 70.5 29.5t29.5 70.5v148l200 200v-298q0 -165 -93.5 -257.5t-256.5 -92.5h-400q-165 0 -257.5 92.5t-92.5 257.5v400q0 165 92.5 257.5t257.5 92.5h300z" />
<glyph unicode="&#xe165;" d="M600 1186q119 0 227.5 -46.5t187 -125t125 -187t46.5 -227.5t-46.5 -227.5t-125 -187t-187 -125t-227.5 -46.5t-227.5 46.5t-187 125t-125 187t-46.5 227.5t46.5 227.5t125 187t187 125t227.5 46.5zM600 1022q-115 0 -212 -56.5t-153.5 -153.5t-56.5 -212t56.5 -212 t153.5 -153.5t212 -56.5t212 56.5t153.5 153.5t56.5 212t-56.5 212t-153.5 153.5t-212 56.5zM600 794q80 0 137 -57t57 -137t-57 -137t-137 -57t-137 57t-57 137t57 137t137 57z" />
<glyph unicode="&#xe166;" d="M450 1200h200q21 0 35.5 -14.5t14.5 -35.5v-350h245q20 0 25 -11t-9 -26l-383 -426q-14 -15 -33.5 -15t-32.5 15l-379 426q-13 15 -8.5 26t25.5 11h250v350q0 21 14.5 35.5t35.5 14.5zM50 300h1000q21 0 35.5 -14.5t14.5 -35.5v-250h-1100v250q0 21 14.5 35.5t35.5 14.5z M900 200v-50h100v50h-100z" />
<glyph unicode="&#xe167;" d="M583 1182l378 -435q14 -15 9 -31t-26 -16h-244v-250q0 -20 -17 -35t-39 -15h-200q-20 0 -32 14.5t-12 35.5v250h-250q-20 0 -25.5 16.5t8.5 31.5l383 431q14 16 33.5 17t33.5 -14zM50 300h1000q21 0 35.5 -14.5t14.5 -35.5v-250h-1100v250q0 21 14.5 35.5t35.5 14.5z M900 200v-50h100v50h-100z" />
<glyph unicode="&#xe168;" d="M396 723l369 369q7 7 17.5 7t17.5 -7l139 -139q7 -8 7 -18.5t-7 -17.5l-525 -525q-7 -8 -17.5 -8t-17.5 8l-292 291q-7 8 -7 18t7 18l139 139q8 7 18.5 7t17.5 -7zM50 300h1000q21 0 35.5 -14.5t14.5 -35.5v-250h-1100v250q0 21 14.5 35.5t35.5 14.5zM900 200v-50h100v50 h-100z" />
<glyph unicode="&#xe169;" d="M135 1023l142 142q14 14 35 14t35 -14l77 -77l-212 -212l-77 76q-14 15 -14 36t14 35zM655 855l210 210q14 14 24.5 10t10.5 -25l-2 -599q-1 -20 -15.5 -35t-35.5 -15l-597 -1q-21 0 -25 10.5t10 24.5l208 208l-154 155l212 212zM50 300h1000q21 0 35.5 -14.5t14.5 -35.5 v-250h-1100v250q0 21 14.5 35.5t35.5 14.5zM900 200v-50h100v50h-100z" />
<glyph unicode="&#xe170;" d="M350 1200l599 -2q20 -1 35 -15.5t15 -35.5l1 -597q0 -21 -10.5 -25t-24.5 10l-208 208l-155 -154l-212 212l155 154l-210 210q-14 14 -10 24.5t25 10.5zM524 512l-76 -77q-15 -14 -36 -14t-35 14l-142 142q-14 14 -14 35t14 35l77 77zM50 300h1000q21 0 35.5 -14.5 t14.5 -35.5v-250h-1100v250q0 21 14.5 35.5t35.5 14.5zM900 200v-50h100v50h-100z" />
<glyph unicode="&#xe171;" d="M1200 103l-483 276l-314 -399v423h-399l1196 796v-1096zM483 424v-230l683 953z" />
<glyph unicode="&#xe172;" d="M1100 1000v-850q0 -21 -14.5 -35.5t-35.5 -14.5h-150v400h-700v-400h-150q-21 0 -35.5 14.5t-14.5 35.5v1000q0 20 14.5 35t35.5 15h250v-300h500v300h100zM700 1000h-100v200h100v-200z" />
<glyph unicode="&#xe173;" d="M1100 1000l-2 -149l-299 -299l-95 95q-9 9 -21.5 9t-21.5 -9l-149 -147h-312v-400h-150q-21 0 -35.5 14.5t-14.5 35.5v1000q0 20 14.5 35t35.5 15h250v-300h500v300h100zM700 1000h-100v200h100v-200zM1132 638l106 -106q7 -7 7 -17.5t-7 -17.5l-420 -421q-8 -7 -18 -7 t-18 7l-202 203q-8 7 -8 17.5t8 17.5l106 106q7 8 17.5 8t17.5 -8l79 -79l297 297q7 7 17.5 7t17.5 -7z" />
<glyph unicode="&#xe174;" d="M1100 1000v-269l-103 -103l-134 134q-15 15 -33.5 16.5t-34.5 -12.5l-266 -266h-329v-400h-150q-21 0 -35.5 14.5t-14.5 35.5v1000q0 20 14.5 35t35.5 15h250v-300h500v300h100zM700 1000h-100v200h100v-200zM1202 572l70 -70q15 -15 15 -35.5t-15 -35.5l-131 -131 l131 -131q15 -15 15 -35.5t-15 -35.5l-70 -70q-15 -15 -35.5 -15t-35.5 15l-131 131l-131 -131q-15 -15 -35.5 -15t-35.5 15l-70 70q-15 15 -15 35.5t15 35.5l131 131l-131 131q-15 15 -15 35.5t15 35.5l70 70q15 15 35.5 15t35.5 -15l131 -131l131 131q15 15 35.5 15 t35.5 -15z" />
<glyph unicode="&#xe175;" d="M1100 1000v-300h-350q-21 0 -35.5 -14.5t-14.5 -35.5v-150h-500v-400h-150q-21 0 -35.5 14.5t-14.5 35.5v1000q0 20 14.5 35t35.5 15h250v-300h500v300h100zM700 1000h-100v200h100v-200zM850 600h100q21 0 35.5 -14.5t14.5 -35.5v-250h150q21 0 25 -10.5t-10 -24.5 l-230 -230q-14 -14 -35 -14t-35 14l-230 230q-14 14 -10 24.5t25 10.5h150v250q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe176;" d="M1100 1000v-400l-165 165q-14 15 -35 15t-35 -15l-263 -265h-402v-400h-150q-21 0 -35.5 14.5t-14.5 35.5v1000q0 20 14.5 35t35.5 15h250v-300h500v300h100zM700 1000h-100v200h100v-200zM935 565l230 -229q14 -15 10 -25.5t-25 -10.5h-150v-250q0 -20 -14.5 -35 t-35.5 -15h-100q-21 0 -35.5 15t-14.5 35v250h-150q-21 0 -25 10.5t10 25.5l230 229q14 15 35 15t35 -15z" />
<glyph unicode="&#xe177;" d="M50 1100h1100q21 0 35.5 -14.5t14.5 -35.5v-150h-1200v150q0 21 14.5 35.5t35.5 14.5zM1200 800v-550q0 -21 -14.5 -35.5t-35.5 -14.5h-1100q-21 0 -35.5 14.5t-14.5 35.5v550h1200zM100 500v-200h400v200h-400z" />
<glyph unicode="&#xe178;" d="M935 1165l248 -230q14 -14 14 -35t-14 -35l-248 -230q-14 -14 -24.5 -10t-10.5 25v150h-400v200h400v150q0 21 10.5 25t24.5 -10zM200 800h-50q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5h50v-200zM400 800h-100v200h100v-200zM18 435l247 230 q14 14 24.5 10t10.5 -25v-150h400v-200h-400v-150q0 -21 -10.5 -25t-24.5 10l-247 230q-15 14 -15 35t15 35zM900 300h-100v200h100v-200zM1000 500h51q20 0 34.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-34.5 -14.5h-51v200z" />
<glyph unicode="&#xe179;" d="M862 1073l276 116q25 18 43.5 8t18.5 -41v-1106q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v397q-4 1 -11 5t-24 17.5t-30 29t-24 42t-11 56.5v359q0 31 18.5 65t43.5 52zM550 1200q22 0 34.5 -12.5t14.5 -24.5l1 -13v-450q0 -28 -10.5 -59.5 t-25 -56t-29 -45t-25.5 -31.5l-10 -11v-447q0 -21 -14.5 -35.5t-35.5 -14.5h-200q-21 0 -35.5 14.5t-14.5 35.5v447q-4 4 -11 11.5t-24 30.5t-30 46t-24 55t-11 60v450q0 2 0.5 5.5t4 12t8.5 15t14.5 12t22.5 5.5q20 0 32.5 -12.5t14.5 -24.5l3 -13v-350h100v350v5.5t2.5 12 t7 15t15 12t25.5 5.5q23 0 35.5 -12.5t13.5 -24.5l1 -13v-350h100v350q0 2 0.5 5.5t3 12t7 15t15 12t24.5 5.5z" />
<glyph unicode="&#xe180;" d="M1200 1100v-56q-4 0 -11 -0.5t-24 -3t-30 -7.5t-24 -15t-11 -24v-888q0 -22 25 -34.5t50 -13.5l25 -2v-56h-400v56q75 0 87.5 6.5t12.5 43.5v394h-500v-394q0 -37 12.5 -43.5t87.5 -6.5v-56h-400v56q4 0 11 0.5t24 3t30 7.5t24 15t11 24v888q0 22 -25 34.5t-50 13.5 l-25 2v56h400v-56q-75 0 -87.5 -6.5t-12.5 -43.5v-394h500v394q0 37 -12.5 43.5t-87.5 6.5v56h400z" />
<glyph unicode="&#xe181;" d="M675 1000h375q21 0 35.5 -14.5t14.5 -35.5v-150h-105l-295 -98v98l-200 200h-400l100 100h375zM100 900h300q41 0 70.5 -29.5t29.5 -70.5v-500q0 -41 -29.5 -70.5t-70.5 -29.5h-300q-41 0 -70.5 29.5t-29.5 70.5v500q0 41 29.5 70.5t70.5 29.5zM100 800v-200h300v200 h-300zM1100 535l-400 -133v163l400 133v-163zM100 500v-200h300v200h-300zM1100 398v-248q0 -21 -14.5 -35.5t-35.5 -14.5h-375l-100 -100h-375l-100 100h400l200 200h105z" />
<glyph unicode="&#xe182;" d="M17 1007l162 162q17 17 40 14t37 -22l139 -194q14 -20 11 -44.5t-20 -41.5l-119 -118q102 -142 228 -268t267 -227l119 118q17 17 42.5 19t44.5 -12l192 -136q19 -14 22.5 -37.5t-13.5 -40.5l-163 -162q-3 -1 -9.5 -1t-29.5 2t-47.5 6t-62.5 14.5t-77.5 26.5t-90 42.5 t-101.5 60t-111 83t-119 108.5q-74 74 -133.5 150.5t-94.5 138.5t-60 119.5t-34.5 100t-15 74.5t-4.5 48z" />
<glyph unicode="&#xe183;" d="M600 1100q92 0 175 -10.5t141.5 -27t108.5 -36.5t81.5 -40t53.5 -37t31 -27l9 -10v-200q0 -21 -14.5 -33t-34.5 -9l-202 34q-20 3 -34.5 20t-14.5 38v146q-141 24 -300 24t-300 -24v-146q0 -21 -14.5 -38t-34.5 -20l-202 -34q-20 -3 -34.5 9t-14.5 33v200q3 4 9.5 10.5 t31 26t54 37.5t80.5 39.5t109 37.5t141 26.5t175 10.5zM600 795q56 0 97 -9.5t60 -23.5t30 -28t12 -24l1 -10v-50l365 -303q14 -15 24.5 -40t10.5 -45v-212q0 -21 -14.5 -35.5t-35.5 -14.5h-1100q-21 0 -35.5 14.5t-14.5 35.5v212q0 20 10.5 45t24.5 40l365 303v50 q0 4 1 10.5t12 23t30 29t60 22.5t97 10z" />
<glyph unicode="&#xe184;" d="M1100 700l-200 -200h-600l-200 200v500h200v-200h200v200h200v-200h200v200h200v-500zM250 400h700q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-12l137 -100h-950l137 100h-12q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5zM50 100h1100q21 0 35.5 -14.5 t14.5 -35.5v-50h-1200v50q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe185;" d="M700 1100h-100q-41 0 -70.5 -29.5t-29.5 -70.5v-1000h300v1000q0 41 -29.5 70.5t-70.5 29.5zM1100 800h-100q-41 0 -70.5 -29.5t-29.5 -70.5v-700h300v700q0 41 -29.5 70.5t-70.5 29.5zM400 0h-300v400q0 41 29.5 70.5t70.5 29.5h100q41 0 70.5 -29.5t29.5 -70.5v-400z " />
<glyph unicode="&#xe186;" d="M200 1100h700q124 0 212 -88t88 -212v-500q0 -124 -88 -212t-212 -88h-700q-124 0 -212 88t-88 212v500q0 124 88 212t212 88zM100 900v-700h900v700h-900zM500 700h-200v-100h200v-300h-300v100h200v100h-200v300h300v-100zM900 700v-300l-100 -100h-200v500h200z M700 700v-300h100v300h-100z" />
<glyph unicode="&#xe187;" d="M200 1100h700q124 0 212 -88t88 -212v-500q0 -124 -88 -212t-212 -88h-700q-124 0 -212 88t-88 212v500q0 124 88 212t212 88zM100 900v-700h900v700h-900zM500 300h-100v200h-100v-200h-100v500h100v-200h100v200h100v-500zM900 700v-300l-100 -100h-200v500h200z M700 700v-300h100v300h-100z" />
<glyph unicode="&#xe188;" d="M200 1100h700q124 0 212 -88t88 -212v-500q0 -124 -88 -212t-212 -88h-700q-124 0 -212 88t-88 212v500q0 124 88 212t212 88zM100 900v-700h900v700h-900zM500 700h-200v-300h200v-100h-300v500h300v-100zM900 700h-200v-300h200v-100h-300v500h300v-100z" />
<glyph unicode="&#xe189;" d="M200 1100h700q124 0 212 -88t88 -212v-500q0 -124 -88 -212t-212 -88h-700q-124 0 -212 88t-88 212v500q0 124 88 212t212 88zM100 900v-700h900v700h-900zM500 400l-300 150l300 150v-300zM900 550l-300 -150v300z" />
<glyph unicode="&#xe190;" d="M200 1100h700q124 0 212 -88t88 -212v-500q0 -124 -88 -212t-212 -88h-700q-124 0 -212 88t-88 212v500q0 124 88 212t212 88zM100 900v-700h900v700h-900zM900 300h-700v500h700v-500zM800 700h-130q-38 0 -66.5 -43t-28.5 -108t27 -107t68 -42h130v300zM300 700v-300 h130q41 0 68 42t27 107t-28.5 108t-66.5 43h-130z" />
<glyph unicode="&#xe191;" d="M200 1100h700q124 0 212 -88t88 -212v-500q0 -124 -88 -212t-212 -88h-700q-124 0 -212 88t-88 212v500q0 124 88 212t212 88zM100 900v-700h900v700h-900zM500 700h-200v-100h200v-300h-300v100h200v100h-200v300h300v-100zM900 300h-100v400h-100v100h200v-500z M700 300h-100v100h100v-100z" />
<glyph unicode="&#xe192;" d="M200 1100h700q124 0 212 -88t88 -212v-500q0 -124 -88 -212t-212 -88h-700q-124 0 -212 88t-88 212v500q0 124 88 212t212 88zM100 900v-700h900v700h-900zM300 700h200v-400h-300v500h100v-100zM900 300h-100v400h-100v100h200v-500zM300 600v-200h100v200h-100z M700 300h-100v100h100v-100z" />
<glyph unicode="&#xe193;" d="M200 1100h700q124 0 212 -88t88 -212v-500q0 -124 -88 -212t-212 -88h-700q-124 0 -212 88t-88 212v500q0 124 88 212t212 88zM100 900v-700h900v700h-900zM500 500l-199 -200h-100v50l199 200v150h-200v100h300v-300zM900 300h-100v400h-100v100h200v-500zM701 300h-100 v100h100v-100z" />
<glyph unicode="&#xe194;" d="M600 1191q120 0 229.5 -47t188.5 -126t126 -188.5t47 -229.5t-47 -229.5t-126 -188.5t-188.5 -126t-229.5 -47t-229.5 47t-188.5 126t-126 188.5t-47 229.5t47 229.5t126 188.5t188.5 126t229.5 47zM600 1021q-114 0 -211 -56.5t-153.5 -153.5t-56.5 -211t56.5 -211 t153.5 -153.5t211 -56.5t211 56.5t153.5 153.5t56.5 211t-56.5 211t-153.5 153.5t-211 56.5zM800 700h-300v-200h300v-100h-300l-100 100v200l100 100h300v-100z" />
<glyph unicode="&#xe195;" d="M600 1191q120 0 229.5 -47t188.5 -126t126 -188.5t47 -229.5t-47 -229.5t-126 -188.5t-188.5 -126t-229.5 -47t-229.5 47t-188.5 126t-126 188.5t-47 229.5t47 229.5t126 188.5t188.5 126t229.5 47zM600 1021q-114 0 -211 -56.5t-153.5 -153.5t-56.5 -211t56.5 -211 t153.5 -153.5t211 -56.5t211 56.5t153.5 153.5t56.5 211t-56.5 211t-153.5 153.5t-211 56.5zM800 700v-100l-50 -50l100 -100v-50h-100l-100 100h-150v-100h-100v400h300zM500 700v-100h200v100h-200z" />
<glyph unicode="&#xe197;" d="M503 1089q110 0 200.5 -59.5t134.5 -156.5q44 14 90 14q120 0 205 -86.5t85 -207t-85 -207t-205 -86.5h-128v250q0 21 -14.5 35.5t-35.5 14.5h-300q-21 0 -35.5 -14.5t-14.5 -35.5v-250h-222q-80 0 -136 57.5t-56 136.5q0 69 43 122.5t108 67.5q-2 19 -2 37q0 100 49 185 t134 134t185 49zM525 500h150q10 0 17.5 -7.5t7.5 -17.5v-275h137q21 0 26 -11.5t-8 -27.5l-223 -244q-13 -16 -32 -16t-32 16l-223 244q-13 16 -8 27.5t26 11.5h137v275q0 10 7.5 17.5t17.5 7.5z" />
<glyph unicode="&#xe198;" d="M502 1089q110 0 201 -59.5t135 -156.5q43 15 89 15q121 0 206 -86.5t86 -206.5q0 -99 -60 -181t-150 -110l-378 360q-13 16 -31.5 16t-31.5 -16l-381 -365h-9q-79 0 -135.5 57.5t-56.5 136.5q0 69 43 122.5t108 67.5q-2 19 -2 38q0 100 49 184.5t133.5 134t184.5 49.5z M632 467l223 -228q13 -16 8 -27.5t-26 -11.5h-137v-275q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v275h-137q-21 0 -26 11.5t8 27.5q199 204 223 228q19 19 31.5 19t32.5 -19z" />
<glyph unicode="&#xe199;" d="M700 100v100h400l-270 300h170l-270 300h170l-300 333l-300 -333h170l-270 -300h170l-270 -300h400v-100h-50q-21 0 -35.5 -14.5t-14.5 -35.5v-50h400v50q0 21 -14.5 35.5t-35.5 14.5h-50z" />
<glyph unicode="&#xe200;" d="M600 1179q94 0 167.5 -56.5t99.5 -145.5q89 -6 150.5 -71.5t61.5 -155.5q0 -61 -29.5 -112.5t-79.5 -82.5q9 -29 9 -55q0 -74 -52.5 -126.5t-126.5 -52.5q-55 0 -100 30v-251q21 0 35.5 -14.5t14.5 -35.5v-50h-300v50q0 21 14.5 35.5t35.5 14.5v251q-45 -30 -100 -30 q-74 0 -126.5 52.5t-52.5 126.5q0 18 4 38q-47 21 -75.5 65t-28.5 97q0 74 52.5 126.5t126.5 52.5q5 0 23 -2q0 2 -1 10t-1 13q0 116 81.5 197.5t197.5 81.5z" />
<glyph unicode="&#xe201;" d="M1010 1010q111 -111 150.5 -260.5t0 -299t-150.5 -260.5q-83 -83 -191.5 -126.5t-218.5 -43.5t-218.5 43.5t-191.5 126.5q-111 111 -150.5 260.5t0 299t150.5 260.5q83 83 191.5 126.5t218.5 43.5t218.5 -43.5t191.5 -126.5zM476 1065q-4 0 -8 -1q-121 -34 -209.5 -122.5 t-122.5 -209.5q-4 -12 2.5 -23t18.5 -14l36 -9q3 -1 7 -1q23 0 29 22q27 96 98 166q70 71 166 98q11 3 17.5 13.5t3.5 22.5l-9 35q-3 13 -14 19q-7 4 -15 4zM512 920q-4 0 -9 -2q-80 -24 -138.5 -82.5t-82.5 -138.5q-4 -13 2 -24t19 -14l34 -9q4 -1 8 -1q22 0 28 21 q18 58 58.5 98.5t97.5 58.5q12 3 18 13.5t3 21.5l-9 35q-3 12 -14 19q-7 4 -15 4zM719.5 719.5q-49.5 49.5 -119.5 49.5t-119.5 -49.5t-49.5 -119.5t49.5 -119.5t119.5 -49.5t119.5 49.5t49.5 119.5t-49.5 119.5zM855 551q-22 0 -28 -21q-18 -58 -58.5 -98.5t-98.5 -57.5 q-11 -4 -17 -14.5t-3 -21.5l9 -35q3 -12 14 -19q7 -4 15 -4q4 0 9 2q80 24 138.5 82.5t82.5 138.5q4 13 -2.5 24t-18.5 14l-34 9q-4 1 -8 1zM1000 515q-23 0 -29 -22q-27 -96 -98 -166q-70 -71 -166 -98q-11 -3 -17.5 -13.5t-3.5 -22.5l9 -35q3 -13 14 -19q7 -4 15 -4 q4 0 8 1q121 34 209.5 122.5t122.5 209.5q4 12 -2.5 23t-18.5 14l-36 9q-3 1 -7 1z" />
<glyph unicode="&#xe202;" d="M700 800h300v-380h-180v200h-340v-200h-380v755q0 10 7.5 17.5t17.5 7.5h575v-400zM1000 900h-200v200zM700 300h162l-212 -212l-212 212h162v200h100v-200zM520 0h-395q-10 0 -17.5 7.5t-7.5 17.5v395zM1000 220v-195q0 -10 -7.5 -17.5t-17.5 -7.5h-195z" />
<glyph unicode="&#xe203;" d="M700 800h300v-520l-350 350l-550 -550v1095q0 10 7.5 17.5t17.5 7.5h575v-400zM1000 900h-200v200zM862 200h-162v-200h-100v200h-162l212 212zM480 0h-355q-10 0 -17.5 7.5t-7.5 17.5v55h380v-80zM1000 80v-55q0 -10 -7.5 -17.5t-17.5 -7.5h-155v80h180z" />
<glyph unicode="&#xe204;" d="M1162 800h-162v-200h100l100 -100h-300v300h-162l212 212zM200 800h200q27 0 40 -2t29.5 -10.5t23.5 -30t7 -57.5h300v-100h-600l-200 -350v450h100q0 36 7 57.5t23.5 30t29.5 10.5t40 2zM800 400h240l-240 -400h-800l300 500h500v-100z" />
<glyph unicode="&#xe205;" d="M650 1100h100q21 0 35.5 -14.5t14.5 -35.5v-50h50q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-300q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5h50v50q0 21 14.5 35.5t35.5 14.5zM1000 850v150q41 0 70.5 -29.5t29.5 -70.5v-800 q0 -41 -29.5 -70.5t-70.5 -29.5h-600q-1 0 -20 4l246 246l-326 326v324q0 41 29.5 70.5t70.5 29.5v-150q0 -62 44 -106t106 -44h300q62 0 106 44t44 106zM412 250l-212 -212v162h-200v100h200v162z" />
<glyph unicode="&#xe206;" d="M450 1100h100q21 0 35.5 -14.5t14.5 -35.5v-50h50q21 0 35.5 -14.5t14.5 -35.5v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-300q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5h50v50q0 21 14.5 35.5t35.5 14.5zM800 850v150q41 0 70.5 -29.5t29.5 -70.5v-500 h-200v-300h200q0 -36 -7 -57.5t-23.5 -30t-29.5 -10.5t-40 -2h-600q-41 0 -70.5 29.5t-29.5 70.5v800q0 41 29.5 70.5t70.5 29.5v-150q0 -62 44 -106t106 -44h300q62 0 106 44t44 106zM1212 250l-212 -212v162h-200v100h200v162z" />
<glyph unicode="&#xe209;" d="M658 1197l637 -1104q23 -38 7 -65.5t-60 -27.5h-1276q-44 0 -60 27.5t7 65.5l637 1104q22 39 54 39t54 -39zM704 800h-208q-20 0 -32 -14.5t-8 -34.5l58 -302q4 -20 21.5 -34.5t37.5 -14.5h54q20 0 37.5 14.5t21.5 34.5l58 302q4 20 -8 34.5t-32 14.5zM500 300v-100h200 v100h-200z" />
<glyph unicode="&#xe210;" d="M425 1100h250q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5zM425 800h250q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5 t17.5 7.5zM825 800h250q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5zM25 500h250q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v150 q0 10 7.5 17.5t17.5 7.5zM425 500h250q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5zM825 500h250q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5 v150q0 10 7.5 17.5t17.5 7.5zM25 200h250q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5zM425 200h250q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5 t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5zM825 200h250q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-250q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5z" />
<glyph unicode="&#xe211;" d="M700 1200h100v-200h-100v-100h350q62 0 86.5 -39.5t-3.5 -94.5l-66 -132q-41 -83 -81 -134h-772q-40 51 -81 134l-66 132q-28 55 -3.5 94.5t86.5 39.5h350v100h-100v200h100v100h200v-100zM250 400h700q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-12l137 -100 h-950l138 100h-13q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5zM50 100h1100q21 0 35.5 -14.5t14.5 -35.5v-50h-1200v50q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe212;" d="M600 1300q40 0 68.5 -29.5t28.5 -70.5h-194q0 41 28.5 70.5t68.5 29.5zM443 1100h314q18 -37 18 -75q0 -8 -3 -25h328q41 0 44.5 -16.5t-30.5 -38.5l-175 -145h-678l-178 145q-34 22 -29 38.5t46 16.5h328q-3 17 -3 25q0 38 18 75zM250 700h700q21 0 35.5 -14.5 t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-150v-200l275 -200h-950l275 200v200h-150q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5zM50 100h1100q21 0 35.5 -14.5t14.5 -35.5v-50h-1200v50q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe213;" d="M600 1181q75 0 128 -53t53 -128t-53 -128t-128 -53t-128 53t-53 128t53 128t128 53zM602 798h46q34 0 55.5 -28.5t21.5 -86.5q0 -76 39 -183h-324q39 107 39 183q0 58 21.5 86.5t56.5 28.5h45zM250 400h700q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-13 l138 -100h-950l137 100h-12q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5zM50 100h1100q21 0 35.5 -14.5t14.5 -35.5v-50h-1200v50q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe214;" d="M600 1300q47 0 92.5 -53.5t71 -123t25.5 -123.5q0 -78 -55.5 -133.5t-133.5 -55.5t-133.5 55.5t-55.5 133.5q0 62 34 143l144 -143l111 111l-163 163q34 26 63 26zM602 798h46q34 0 55.5 -28.5t21.5 -86.5q0 -76 39 -183h-324q39 107 39 183q0 58 21.5 86.5t56.5 28.5h45 zM250 400h700q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-13l138 -100h-950l137 100h-12q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5zM50 100h1100q21 0 35.5 -14.5t14.5 -35.5v-50h-1200v50q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe215;" d="M600 1200l300 -161v-139h-300q0 -57 18.5 -108t50 -91.5t63 -72t70 -67.5t57.5 -61h-530q-60 83 -90.5 177.5t-30.5 178.5t33 164.5t87.5 139.5t126 96.5t145.5 41.5v-98zM250 400h700q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-13l138 -100h-950l137 100 h-12q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5zM50 100h1100q21 0 35.5 -14.5t14.5 -35.5v-50h-1200v50q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe216;" d="M600 1300q41 0 70.5 -29.5t29.5 -70.5v-78q46 -26 73 -72t27 -100v-50h-400v50q0 54 27 100t73 72v78q0 41 29.5 70.5t70.5 29.5zM400 800h400q54 0 100 -27t72 -73h-172v-100h200v-100h-200v-100h200v-100h-200v-100h200q0 -83 -58.5 -141.5t-141.5 -58.5h-400 q-83 0 -141.5 58.5t-58.5 141.5v400q0 83 58.5 141.5t141.5 58.5z" />
<glyph unicode="&#xe218;" d="M150 1100h900q21 0 35.5 -14.5t14.5 -35.5v-500q0 -21 -14.5 -35.5t-35.5 -14.5h-900q-21 0 -35.5 14.5t-14.5 35.5v500q0 21 14.5 35.5t35.5 14.5zM125 400h950q10 0 17.5 -7.5t7.5 -17.5v-50q0 -10 -7.5 -17.5t-17.5 -7.5h-283l224 -224q13 -13 13 -31.5t-13 -32 t-31.5 -13.5t-31.5 13l-88 88h-524l-87 -88q-13 -13 -32 -13t-32 13.5t-13 32t13 31.5l224 224h-289q-10 0 -17.5 7.5t-7.5 17.5v50q0 10 7.5 17.5t17.5 7.5zM541 300l-100 -100h324l-100 100h-124z" />
<glyph unicode="&#xe219;" d="M200 1100h800q83 0 141.5 -58.5t58.5 -141.5v-200h-100q0 41 -29.5 70.5t-70.5 29.5h-250q-41 0 -70.5 -29.5t-29.5 -70.5h-100q0 41 -29.5 70.5t-70.5 29.5h-250q-41 0 -70.5 -29.5t-29.5 -70.5h-100v200q0 83 58.5 141.5t141.5 58.5zM100 600h1000q41 0 70.5 -29.5 t29.5 -70.5v-300h-1200v300q0 41 29.5 70.5t70.5 29.5zM300 100v-50q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v50h200zM1100 100v-50q0 -21 -14.5 -35.5t-35.5 -14.5h-100q-21 0 -35.5 14.5t-14.5 35.5v50h200z" />
<glyph unicode="&#xe221;" d="M480 1165l682 -683q31 -31 31 -75.5t-31 -75.5l-131 -131h-481l-517 518q-32 31 -32 75.5t32 75.5l295 296q31 31 75.5 31t76.5 -31zM108 794l342 -342l303 304l-341 341zM250 100h800q21 0 35.5 -14.5t14.5 -35.5v-50h-900v50q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe223;" d="M1057 647l-189 506q-8 19 -27.5 33t-40.5 14h-400q-21 0 -40.5 -14t-27.5 -33l-189 -506q-8 -19 1.5 -33t30.5 -14h625v-150q0 -21 14.5 -35.5t35.5 -14.5t35.5 14.5t14.5 35.5v150h125q21 0 30.5 14t1.5 33zM897 0h-595v50q0 21 14.5 35.5t35.5 14.5h50v50 q0 21 14.5 35.5t35.5 14.5h48v300h200v-300h47q21 0 35.5 -14.5t14.5 -35.5v-50h50q21 0 35.5 -14.5t14.5 -35.5v-50z" />
<glyph unicode="&#xe224;" d="M900 800h300v-575q0 -10 -7.5 -17.5t-17.5 -7.5h-375v591l-300 300v84q0 10 7.5 17.5t17.5 7.5h375v-400zM1200 900h-200v200zM400 600h300v-575q0 -10 -7.5 -17.5t-17.5 -7.5h-650q-10 0 -17.5 7.5t-7.5 17.5v950q0 10 7.5 17.5t17.5 7.5h375v-400zM700 700h-200v200z " />
<glyph unicode="&#xe225;" d="M484 1095h195q75 0 146 -32.5t124 -86t89.5 -122.5t48.5 -142q18 -14 35 -20q31 -10 64.5 6.5t43.5 48.5q10 34 -15 71q-19 27 -9 43q5 8 12.5 11t19 -1t23.5 -16q41 -44 39 -105q-3 -63 -46 -106.5t-104 -43.5h-62q-7 -55 -35 -117t-56 -100l-39 -234q-3 -20 -20 -34.5 t-38 -14.5h-100q-21 0 -33 14.5t-9 34.5l12 70q-49 -14 -91 -14h-195q-24 0 -65 8l-11 -64q-3 -20 -20 -34.5t-38 -14.5h-100q-21 0 -33 14.5t-9 34.5l26 157q-84 74 -128 175l-159 53q-19 7 -33 26t-14 40v50q0 21 14.5 35.5t35.5 14.5h124q11 87 56 166l-111 95 q-16 14 -12.5 23.5t24.5 9.5h203q116 101 250 101zM675 1000h-250q-10 0 -17.5 -7.5t-7.5 -17.5v-50q0 -10 7.5 -17.5t17.5 -7.5h250q10 0 17.5 7.5t7.5 17.5v50q0 10 -7.5 17.5t-17.5 7.5z" />
<glyph unicode="&#xe226;" d="M641 900l423 247q19 8 42 2.5t37 -21.5l32 -38q14 -15 12.5 -36t-17.5 -34l-139 -120h-390zM50 1100h106q67 0 103 -17t66 -71l102 -212h823q21 0 35.5 -14.5t14.5 -35.5v-50q0 -21 -14 -40t-33 -26l-737 -132q-23 -4 -40 6t-26 25q-42 67 -100 67h-300q-62 0 -106 44 t-44 106v200q0 62 44 106t106 44zM173 928h-80q-19 0 -28 -14t-9 -35v-56q0 -51 42 -51h134q16 0 21.5 8t5.5 24q0 11 -16 45t-27 51q-18 28 -43 28zM550 727q-32 0 -54.5 -22.5t-22.5 -54.5t22.5 -54.5t54.5 -22.5t54.5 22.5t22.5 54.5t-22.5 54.5t-54.5 22.5zM130 389 l152 130q18 19 34 24t31 -3.5t24.5 -17.5t25.5 -28q28 -35 50.5 -51t48.5 -13l63 5l48 -179q13 -61 -3.5 -97.5t-67.5 -79.5l-80 -69q-47 -40 -109 -35.5t-103 51.5l-130 151q-40 47 -35.5 109.5t51.5 102.5zM380 377l-102 -88q-31 -27 2 -65l37 -43q13 -15 27.5 -19.5 t31.5 6.5l61 53q19 16 14 49q-2 20 -12 56t-17 45q-11 12 -19 14t-23 -8z" />
<glyph unicode="&#xe227;" d="M625 1200h150q10 0 17.5 -7.5t7.5 -17.5v-109q79 -33 131 -87.5t53 -128.5q1 -46 -15 -84.5t-39 -61t-46 -38t-39 -21.5l-17 -6q6 0 15 -1.5t35 -9t50 -17.5t53 -30t50 -45t35.5 -64t14.5 -84q0 -59 -11.5 -105.5t-28.5 -76.5t-44 -51t-49.5 -31.5t-54.5 -16t-49.5 -6.5 t-43.5 -1v-75q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v75h-100v-75q0 -10 -7.5 -17.5t-17.5 -7.5h-150q-10 0 -17.5 7.5t-7.5 17.5v75h-175q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5h75v600h-75q-10 0 -17.5 7.5t-7.5 17.5v150 q0 10 7.5 17.5t17.5 7.5h175v75q0 10 7.5 17.5t17.5 7.5h150q10 0 17.5 -7.5t7.5 -17.5v-75h100v75q0 10 7.5 17.5t17.5 7.5zM400 900v-200h263q28 0 48.5 10.5t30 25t15 29t5.5 25.5l1 10q0 4 -0.5 11t-6 24t-15 30t-30 24t-48.5 11h-263zM400 500v-200h363q28 0 48.5 10.5 t30 25t15 29t5.5 25.5l1 10q0 4 -0.5 11t-6 24t-15 30t-30 24t-48.5 11h-363z" />
<glyph unicode="&#xe230;" d="M212 1198h780q86 0 147 -61t61 -147v-416q0 -51 -18 -142.5t-36 -157.5l-18 -66q-29 -87 -93.5 -146.5t-146.5 -59.5h-572q-82 0 -147 59t-93 147q-8 28 -20 73t-32 143.5t-20 149.5v416q0 86 61 147t147 61zM600 1045q-70 0 -132.5 -11.5t-105.5 -30.5t-78.5 -41.5 t-57 -45t-36 -41t-20.5 -30.5l-6 -12l156 -243h560l156 243q-2 5 -6 12.5t-20 29.5t-36.5 42t-57 44.5t-79 42t-105 29.5t-132.5 12zM762 703h-157l195 261z" />
<glyph unicode="&#xe231;" d="M475 1300h150q103 0 189 -86t86 -189v-500q0 -41 -42 -83t-83 -42h-450q-41 0 -83 42t-42 83v500q0 103 86 189t189 86zM700 300v-225q0 -21 -27 -48t-48 -27h-150q-21 0 -48 27t-27 48v225h300z" />
<glyph unicode="&#xe232;" d="M475 1300h96q0 -150 89.5 -239.5t239.5 -89.5v-446q0 -41 -42 -83t-83 -42h-450q-41 0 -83 42t-42 83v500q0 103 86 189t189 86zM700 300v-225q0 -21 -27 -48t-48 -27h-150q-21 0 -48 27t-27 48v225h300z" />
<glyph unicode="&#xe233;" d="M1294 767l-638 -283l-378 170l-78 -60v-224l100 -150v-199l-150 148l-150 -149v200l100 150v250q0 4 -0.5 10.5t0 9.5t1 8t3 8t6.5 6l47 40l-147 65l642 283zM1000 380l-350 -166l-350 166v147l350 -165l350 165v-147z" />
<glyph unicode="&#xe234;" d="M250 800q62 0 106 -44t44 -106t-44 -106t-106 -44t-106 44t-44 106t44 106t106 44zM650 800q62 0 106 -44t44 -106t-44 -106t-106 -44t-106 44t-44 106t44 106t106 44zM1050 800q62 0 106 -44t44 -106t-44 -106t-106 -44t-106 44t-44 106t44 106t106 44z" />
<glyph unicode="&#xe235;" d="M550 1100q62 0 106 -44t44 -106t-44 -106t-106 -44t-106 44t-44 106t44 106t106 44zM550 700q62 0 106 -44t44 -106t-44 -106t-106 -44t-106 44t-44 106t44 106t106 44zM550 300q62 0 106 -44t44 -106t-44 -106t-106 -44t-106 44t-44 106t44 106t106 44z" />
<glyph unicode="&#xe236;" d="M125 1100h950q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-950q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5zM125 700h950q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-950q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5 t17.5 7.5zM125 300h950q10 0 17.5 -7.5t7.5 -17.5v-150q0 -10 -7.5 -17.5t-17.5 -7.5h-950q-10 0 -17.5 7.5t-7.5 17.5v150q0 10 7.5 17.5t17.5 7.5z" />
<glyph unicode="&#xe237;" d="M350 1200h500q162 0 256 -93.5t94 -256.5v-500q0 -165 -93.5 -257.5t-256.5 -92.5h-500q-165 0 -257.5 92.5t-92.5 257.5v500q0 165 92.5 257.5t257.5 92.5zM900 1000h-600q-41 0 -70.5 -29.5t-29.5 -70.5v-600q0 -41 29.5 -70.5t70.5 -29.5h600q41 0 70.5 29.5 t29.5 70.5v600q0 41 -29.5 70.5t-70.5 29.5zM350 900h500q21 0 35.5 -14.5t14.5 -35.5v-300q0 -21 -14.5 -35.5t-35.5 -14.5h-500q-21 0 -35.5 14.5t-14.5 35.5v300q0 21 14.5 35.5t35.5 14.5zM400 800v-200h400v200h-400z" />
<glyph unicode="&#xe238;" d="M150 1100h1000q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-50v-200h50q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-50v-200h50q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5t-35.5 -14.5h-50v-200h50q21 0 35.5 -14.5t14.5 -35.5t-14.5 -35.5 t-35.5 -14.5h-1000q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5h50v200h-50q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5h50v200h-50q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5h50v200h-50q-21 0 -35.5 14.5t-14.5 35.5t14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe239;" d="M650 1187q87 -67 118.5 -156t0 -178t-118.5 -155q-87 66 -118.5 155t0 178t118.5 156zM300 800q124 0 212 -88t88 -212q-124 0 -212 88t-88 212zM1000 800q0 -124 -88 -212t-212 -88q0 124 88 212t212 88zM300 500q124 0 212 -88t88 -212q-124 0 -212 88t-88 212z M1000 500q0 -124 -88 -212t-212 -88q0 124 88 212t212 88zM700 199v-144q0 -21 -14.5 -35.5t-35.5 -14.5t-35.5 14.5t-14.5 35.5v142q40 -4 43 -4q17 0 57 6z" />
<glyph unicode="&#xe240;" d="M745 878l69 19q25 6 45 -12l298 -295q11 -11 15 -26.5t-2 -30.5q-5 -14 -18 -23.5t-28 -9.5h-8q1 0 1 -13q0 -29 -2 -56t-8.5 -62t-20 -63t-33 -53t-51 -39t-72.5 -14h-146q-184 0 -184 288q0 24 10 47q-20 4 -62 4t-63 -4q11 -24 11 -47q0 -288 -184 -288h-142 q-48 0 -84.5 21t-56 51t-32 71.5t-16 75t-3.5 68.5q0 13 2 13h-7q-15 0 -27.5 9.5t-18.5 23.5q-6 15 -2 30.5t15 25.5l298 296q20 18 46 11l76 -19q20 -5 30.5 -22.5t5.5 -37.5t-22.5 -31t-37.5 -5l-51 12l-182 -193h891l-182 193l-44 -12q-20 -5 -37.5 6t-22.5 31t6 37.5 t31 22.5z" />
<glyph unicode="&#xe241;" d="M1200 900h-50q0 21 -4 37t-9.5 26.5t-18 17.5t-22 11t-28.5 5.5t-31 2t-37 0.5h-200v-850q0 -22 25 -34.5t50 -13.5l25 -2v-100h-400v100q4 0 11 0.5t24 3t30 7t24 15t11 24.5v850h-200q-25 0 -37 -0.5t-31 -2t-28.5 -5.5t-22 -11t-18 -17.5t-9.5 -26.5t-4 -37h-50v300 h1000v-300zM500 450h-25q0 15 -4 24.5t-9 14.5t-17 7.5t-20 3t-25 0.5h-100v-425q0 -11 12.5 -17.5t25.5 -7.5h12v-50h-200v50q50 0 50 25v425h-100q-17 0 -25 -0.5t-20 -3t-17 -7.5t-9 -14.5t-4 -24.5h-25v150h500v-150z" />
<glyph unicode="&#xe242;" d="M1000 300v50q-25 0 -55 32q-14 14 -25 31t-16 27l-4 11l-289 747h-69l-300 -754q-18 -35 -39 -56q-9 -9 -24.5 -18.5t-26.5 -14.5l-11 -5v-50h273v50q-49 0 -78.5 21.5t-11.5 67.5l69 176h293l61 -166q13 -34 -3.5 -66.5t-55.5 -32.5v-50h312zM412 691l134 342l121 -342 h-255zM1100 150v-100q0 -21 -14.5 -35.5t-35.5 -14.5h-1000q-21 0 -35.5 14.5t-14.5 35.5v100q0 21 14.5 35.5t35.5 14.5h1000q21 0 35.5 -14.5t14.5 -35.5z" />
<glyph unicode="&#xe243;" d="M50 1200h1100q21 0 35.5 -14.5t14.5 -35.5v-1100q0 -21 -14.5 -35.5t-35.5 -14.5h-1100q-21 0 -35.5 14.5t-14.5 35.5v1100q0 21 14.5 35.5t35.5 14.5zM611 1118h-70q-13 0 -18 -12l-299 -753q-17 -32 -35 -51q-18 -18 -56 -34q-12 -5 -12 -18v-50q0 -8 5.5 -14t14.5 -6 h273q8 0 14 6t6 14v50q0 8 -6 14t-14 6q-55 0 -71 23q-10 14 0 39l63 163h266l57 -153q11 -31 -6 -55q-12 -17 -36 -17q-8 0 -14 -6t-6 -14v-50q0 -8 6 -14t14 -6h313q8 0 14 6t6 14v50q0 7 -5.5 13t-13.5 7q-17 0 -42 25q-25 27 -40 63h-1l-288 748q-5 12 -19 12zM639 611 h-197l103 264z" />
<glyph unicode="&#xe244;" d="M1200 1100h-1200v100h1200v-100zM50 1000h400q21 0 35.5 -14.5t14.5 -35.5v-900q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-21 0 -35.5 14.5t-14.5 35.5v900q0 21 14.5 35.5t35.5 14.5zM650 1000h400q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-400 q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5zM700 900v-300h300v300h-300z" />
<glyph unicode="&#xe245;" d="M50 1200h400q21 0 35.5 -14.5t14.5 -35.5v-900q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-21 0 -35.5 14.5t-14.5 35.5v900q0 21 14.5 35.5t35.5 14.5zM650 700h400q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-21 0 -35.5 14.5t-14.5 35.5v400 q0 21 14.5 35.5t35.5 14.5zM700 600v-300h300v300h-300zM1200 0h-1200v100h1200v-100z" />
<glyph unicode="&#xe246;" d="M50 1000h400q21 0 35.5 -14.5t14.5 -35.5v-350h100v150q0 21 14.5 35.5t35.5 14.5h400q21 0 35.5 -14.5t14.5 -35.5v-150h100v-100h-100v-150q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-21 0 -35.5 14.5t-14.5 35.5v150h-100v-350q0 -21 -14.5 -35.5t-35.5 -14.5h-400 q-21 0 -35.5 14.5t-14.5 35.5v800q0 21 14.5 35.5t35.5 14.5zM700 700v-300h300v300h-300z" />
<glyph unicode="&#xe247;" d="M100 0h-100v1200h100v-1200zM250 1100h400q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5zM300 1000v-300h300v300h-300zM250 500h900q21 0 35.5 -14.5t14.5 -35.5v-400 q0 -21 -14.5 -35.5t-35.5 -14.5h-900q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe248;" d="M600 1100h150q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-150v-100h450q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-900q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5h350v100h-150q-21 0 -35.5 14.5 t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5h150v100h100v-100zM400 1000v-300h300v300h-300z" />
<glyph unicode="&#xe249;" d="M1200 0h-100v1200h100v-1200zM550 1100h400q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-400q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5zM600 1000v-300h300v300h-300zM50 500h900q21 0 35.5 -14.5t14.5 -35.5v-400 q0 -21 -14.5 -35.5t-35.5 -14.5h-900q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5z" />
<glyph unicode="&#xe250;" d="M865 565l-494 -494q-23 -23 -41 -23q-14 0 -22 13.5t-8 38.5v1000q0 25 8 38.5t22 13.5q18 0 41 -23l494 -494q14 -14 14 -35t-14 -35z" />
<glyph unicode="&#xe251;" d="M335 635l494 494q29 29 50 20.5t21 -49.5v-1000q0 -41 -21 -49.5t-50 20.5l-494 494q-14 14 -14 35t14 35z" />
<glyph unicode="&#xe252;" d="M100 900h1000q41 0 49.5 -21t-20.5 -50l-494 -494q-14 -14 -35 -14t-35 14l-494 494q-29 29 -20.5 50t49.5 21z" />
<glyph unicode="&#xe253;" d="M635 865l494 -494q29 -29 20.5 -50t-49.5 -21h-1000q-41 0 -49.5 21t20.5 50l494 494q14 14 35 14t35 -14z" />
<glyph unicode="&#xe254;" d="M700 741v-182l-692 -323v221l413 193l-413 193v221zM1200 0h-800v200h800v-200z" />
<glyph unicode="&#xe255;" d="M1200 900h-200v-100h200v-100h-300v300h200v100h-200v100h300v-300zM0 700h50q0 21 4 37t9.5 26.5t18 17.5t22 11t28.5 5.5t31 2t37 0.5h100v-550q0 -22 -25 -34.5t-50 -13.5l-25 -2v-100h400v100q-4 0 -11 0.5t-24 3t-30 7t-24 15t-11 24.5v550h100q25 0 37 -0.5t31 -2 t28.5 -5.5t22 -11t18 -17.5t9.5 -26.5t4 -37h50v300h-800v-300z" />
<glyph unicode="&#xe256;" d="M800 700h-50q0 21 -4 37t-9.5 26.5t-18 17.5t-22 11t-28.5 5.5t-31 2t-37 0.5h-100v-550q0 -22 25 -34.5t50 -14.5l25 -1v-100h-400v100q4 0 11 0.5t24 3t30 7t24 15t11 24.5v550h-100q-25 0 -37 -0.5t-31 -2t-28.5 -5.5t-22 -11t-18 -17.5t-9.5 -26.5t-4 -37h-50v300 h800v-300zM1100 200h-200v-100h200v-100h-300v300h200v100h-200v100h300v-300z" />
<glyph unicode="&#xe257;" d="M701 1098h160q16 0 21 -11t-7 -23l-464 -464l464 -464q12 -12 7 -23t-21 -11h-160q-13 0 -23 9l-471 471q-7 8 -7 18t7 18l471 471q10 9 23 9z" />
<glyph unicode="&#xe258;" d="M339 1098h160q13 0 23 -9l471 -471q7 -8 7 -18t-7 -18l-471 -471q-10 -9 -23 -9h-160q-16 0 -21 11t7 23l464 464l-464 464q-12 12 -7 23t21 11z" />
<glyph unicode="&#xe259;" d="M1087 882q11 -5 11 -21v-160q0 -13 -9 -23l-471 -471q-8 -7 -18 -7t-18 7l-471 471q-9 10 -9 23v160q0 16 11 21t23 -7l464 -464l464 464q12 12 23 7z" />
<glyph unicode="&#xe260;" d="M618 993l471 -471q9 -10 9 -23v-160q0 -16 -11 -21t-23 7l-464 464l-464 -464q-12 -12 -23 -7t-11 21v160q0 13 9 23l471 471q8 7 18 7t18 -7z" />
<glyph unicode="&#xf8ff;" d="M1000 1200q0 -124 -88 -212t-212 -88q0 124 88 212t212 88zM450 1000h100q21 0 40 -14t26 -33l79 -194q5 1 16 3q34 6 54 9.5t60 7t65.5 1t61 -10t56.5 -23t42.5 -42t29 -64t5 -92t-19.5 -121.5q-1 -7 -3 -19.5t-11 -50t-20.5 -73t-32.5 -81.5t-46.5 -83t-64 -70 t-82.5 -50q-13 -5 -42 -5t-65.5 2.5t-47.5 2.5q-14 0 -49.5 -3.5t-63 -3.5t-43.5 7q-57 25 -104.5 78.5t-75 111.5t-46.5 112t-26 90l-7 35q-15 63 -18 115t4.5 88.5t26 64t39.5 43.5t52 25.5t58.5 13t62.5 2t59.5 -4.5t55.5 -8l-147 192q-12 18 -5.5 30t27.5 12z" />
<glyph unicode="&#x1f511;" d="M250 1200h600q21 0 35.5 -14.5t14.5 -35.5v-400q0 -21 -14.5 -35.5t-35.5 -14.5h-150v-500l-255 -178q-19 -9 -32 -1t-13 29v650h-150q-21 0 -35.5 14.5t-14.5 35.5v400q0 21 14.5 35.5t35.5 14.5zM400 1100v-100h300v100h-300z" />
<glyph unicode="&#x1f6aa;" d="M250 1200h750q39 0 69.5 -40.5t30.5 -84.5v-933l-700 -117v950l600 125h-700v-1000h-100v1025q0 23 15.5 49t34.5 26zM500 525v-100l100 20v100z" />
</font>
</defs></svg> ) format('svg')}.glyphicon{position:relative;top:1px;display:inline-block;font-family:'Glyphicons Halflings';font-style:normal;font-weight:400;line-height:1;-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale}.glyphicon-asterisk:before{content:"\2a"}.glyphicon-plus:before{content:"\2b"}.glyphicon-eur:before,.glyphicon-euro:before{content:"\20ac"}.glyphicon-minus:before{content:"\2212"}.glyphicon-cloud:before{content:"\2601"}.glyphicon-envelope:before{content:"\2709"}.glyphicon-pencil:before{content:"\270f"}.glyphicon-glass:before{content:"\e001"}.glyphicon-music:before{content:"\e002"}.glyphicon-search:before{content:"\e003"}.glyphicon-heart:before{content:"\e005"}.glyphicon-star:before{content:"\e006"}.glyphicon-star-empty:before{content:"\e007"}.glyphicon-user:before{content:"\e008"}.glyphicon-film:before{content:"\e009"}.glyphicon-th-large:before{content:"\e010"}.glyphicon-th:before{content:"\e011"}.glyphicon-th-list:before{content:"\e012"}.glyphicon-ok:before{content:"\e013"}.glyphicon-remove:before{content:"\e014"}.glyphicon-zoom-in:before{content:"\e015"}.glyphicon-zoom-out:before{content:"\e016"}.glyphicon-off:before{content:"\e017"}.glyphicon-signal:before{content:"\e018"}.glyphicon-cog:before{content:"\e019"}.glyphicon-trash:before{content:"\e020"}.glyphicon-home:before{content:"\e021"}.glyphicon-file:before{content:"\e022"}.glyphicon-time:before{content:"\e023"}.glyphicon-road:before{content:"\e024"}.glyphicon-download-alt:before{content:"\e025"}.glyphicon-download:before{content:"\e026"}.glyphicon-upload:before{content:"\e027"}.glyphicon-inbox:before{content:"\e028"}.glyphicon-play-circle:before{content:"\e029"}.glyphicon-repeat:before{content:"\e030"}.glyphicon-refresh:before{content:"\e031"}.glyphicon-list-alt:before{content:"\e032"}.glyphicon-lock:before{content:"\e033"}.glyphicon-flag:before{content:"\e034"}.glyphicon-headphones:before{content:"\e035"}.glyphicon-volume-off:before{content:"\e036"}.glyphicon-volume-down:before{content:"\e037"}.glyphicon-volume-up:before{content:"\e038"}.glyphicon-qrcode:before{content:"\e039"}.glyphicon-barcode:before{content:"\e040"}.glyphicon-tag:before{content:"\e041"}.glyphicon-tags:before{content:"\e042"}.glyphicon-book:before{content:"\e043"}.glyphicon-bookmark:before{content:"\e044"}.glyphicon-print:before{content:"\e045"}.glyphicon-camera:before{content:"\e046"}.glyphicon-font:before{content:"\e047"}.glyphicon-bold:before{content:"\e048"}.glyphicon-italic:before{content:"\e049"}.glyphicon-text-height:before{content:"\e050"}.glyphicon-text-width:before{content:"\e051"}.glyphicon-align-left:before{content:"\e052"}.glyphicon-align-center:before{content:"\e053"}.glyphicon-align-right:before{content:"\e054"}.glyphicon-align-justify:before{content:"\e055"}.glyphicon-list:before{content:"\e056"}.glyphicon-indent-left:before{content:"\e057"}.glyphicon-indent-right:before{content:"\e058"}.glyphicon-facetime-video:before{content:"\e059"}.glyphicon-picture:before{content:"\e060"}.glyphicon-map-marker:before{content:"\e062"}.glyphicon-adjust:before{content:"\e063"}.glyphicon-tint:before{content:"\e064"}.glyphicon-edit:before{content:"\e065"}.glyphicon-share:before{content:"\e066"}.glyphicon-check:before{content:"\e067"}.glyphicon-move:before{content:"\e068"}.glyphicon-step-backward:before{content:"\e069"}.glyphicon-fast-backward:before{content:"\e070"}.glyphicon-backward:before{content:"\e071"}.glyphicon-play:before{content:"\e072"}.glyphicon-pause:before{content:"\e073"}.glyphicon-stop:before{content:"\e074"}.glyphicon-forward:before{content:"\e075"}.glyphicon-fast-forward:before{content:"\e076"}.glyphicon-step-forward:before{content:"\e077"}.glyphicon-eject:before{content:"\e078"}.glyphicon-chevron-left:before{content:"\e079"}.glyphicon-chevron-right:before{content:"\e080"}.glyphicon-plus-sign:before{content:"\e081"}.glyphicon-minus-sign:before{content:"\e082"}.glyphicon-remove-sign:before{content:"\e083"}.glyphicon-ok-sign:before{content:"\e084"}.glyphicon-question-sign:before{content:"\e085"}.glyphicon-info-sign:before{content:"\e086"}.glyphicon-screenshot:before{content:"\e087"}.glyphicon-remove-circle:before{content:"\e088"}.glyphicon-ok-circle:before{content:"\e089"}.glyphicon-ban-circle:before{content:"\e090"}.glyphicon-arrow-left:before{content:"\e091"}.glyphicon-arrow-right:before{content:"\e092"}.glyphicon-arrow-up:before{content:"\e093"}.glyphicon-arrow-down:before{content:"\e094"}.glyphicon-share-alt:before{content:"\e095"}.glyphicon-resize-full:before{content:"\e096"}.glyphicon-resize-small:before{content:"\e097"}.glyphicon-exclamation-sign:before{content:"\e101"}.glyphicon-gift:before{content:"\e102"}.glyphicon-leaf:before{content:"\e103"}.glyphicon-fire:before{content:"\e104"}.glyphicon-eye-open:before{content:"\e105"}.glyphicon-eye-close:before{content:"\e106"}.glyphicon-warning-sign:before{content:"\e107"}.glyphicon-plane:before{content:"\e108"}.glyphicon-calendar:before{content:"\e109"}.glyphicon-random:before{content:"\e110"}.glyphicon-comment:before{content:"\e111"}.glyphicon-magnet:before{content:"\e112"}.glyphicon-chevron-up:before{content:"\e113"}.glyphicon-chevron-down:before{content:"\e114"}.glyphicon-retweet:before{content:"\e115"}.glyphicon-shopping-cart:before{content:"\e116"}.glyphicon-folder-close:before{content:"\e117"}.glyphicon-folder-open:before{content:"\e118"}.glyphicon-resize-vertical:before{content:"\e119"}.glyphicon-resize-horizontal:before{content:"\e120"}.glyphicon-hdd:before{content:"\e121"}.glyphicon-bullhorn:before{content:"\e122"}.glyphicon-bell:before{content:"\e123"}.glyphicon-certificate:before{content:"\e124"}.glyphicon-thumbs-up:before{content:"\e125"}.glyphicon-thumbs-down:before{content:"\e126"}.glyphicon-hand-right:before{content:"\e127"}.glyphicon-hand-left:before{content:"\e128"}.glyphicon-hand-up:before{content:"\e129"}.glyphicon-hand-down:before{content:"\e130"}.glyphicon-circle-arrow-right:before{content:"\e131"}.glyphicon-circle-arrow-left:before{content:"\e132"}.glyphicon-circle-arrow-up:before{content:"\e133"}.glyphicon-circle-arrow-down:before{content:"\e134"}.glyphicon-globe:before{content:"\e135"}.glyphicon-wrench:before{content:"\e136"}.glyphicon-tasks:before{content:"\e137"}.glyphicon-filter:before{content:"\e138"}.glyphicon-briefcase:before{content:"\e139"}.glyphicon-fullscreen:before{content:"\e140"}.glyphicon-dashboard:before{content:"\e141"}.glyphicon-paperclip:before{content:"\e142"}.glyphicon-heart-empty:before{content:"\e143"}.glyphicon-link:before{content:"\e144"}.glyphicon-phone:before{content:"\e145"}.glyphicon-pushpin:before{content:"\e146"}.glyphicon-usd:before{content:"\e148"}.glyphicon-gbp:before{content:"\e149"}.glyphicon-sort:before{content:"\e150"}.glyphicon-sort-by-alphabet:before{content:"\e151"}.glyphicon-sort-by-alphabet-alt:before{content:"\e152"}.glyphicon-sort-by-order:before{content:"\e153"}.glyphicon-sort-by-order-alt:before{content:"\e154"}.glyphicon-sort-by-attributes:before{content:"\e155"}.glyphicon-sort-by-attributes-alt:before{content:"\e156"}.glyphicon-unchecked:before{content:"\e157"}.glyphicon-expand:before{content:"\e158"}.glyphicon-collapse-down:before{content:"\e159"}.glyphicon-collapse-up:before{content:"\e160"}.glyphicon-log-in:before{content:"\e161"}.glyphicon-flash:before{content:"\e162"}.glyphicon-log-out:before{content:"\e163"}.glyphicon-new-window:before{content:"\e164"}.glyphicon-record:before{content:"\e165"}.glyphicon-save:before{content:"\e166"}.glyphicon-open:before{content:"\e167"}.glyphicon-saved:before{content:"\e168"}.glyphicon-import:before{content:"\e169"}.glyphicon-export:before{content:"\e170"}.glyphicon-send:before{content:"\e171"}.glyphicon-floppy-disk:before{content:"\e172"}.glyphicon-floppy-saved:before{content:"\e173"}.glyphicon-floppy-remove:before{content:"\e174"}.glyphicon-floppy-save:before{content:"\e175"}.glyphicon-floppy-open:before{content:"\e176"}.glyphicon-credit-card:before{content:"\e177"}.glyphicon-transfer:before{content:"\e178"}.glyphicon-cutlery:before{content:"\e179"}.glyphicon-header:before{content:"\e180"}.glyphicon-compressed:before{content:"\e181"}.glyphicon-earphone:before{content:"\e182"}.glyphicon-phone-alt:before{content:"\e183"}.glyphicon-tower:before{content:"\e184"}.glyphicon-stats:before{content:"\e185"}.glyphicon-sd-video:before{content:"\e186"}.glyphicon-hd-video:before{content:"\e187"}.glyphicon-subtitles:before{content:"\e188"}.glyphicon-sound-stereo:before{content:"\e189"}.glyphicon-sound-dolby:before{content:"\e190"}.glyphicon-sound-5-1:before{content:"\e191"}.glyphicon-sound-6-1:before{content:"\e192"}.glyphicon-sound-7-1:before{content:"\e193"}.glyphicon-copyright-mark:before{content:"\e194"}.glyphicon-registration-mark:before{content:"\e195"}.glyphicon-cloud-download:before{content:"\e197"}.glyphicon-cloud-upload:before{content:"\e198"}.glyphicon-tree-conifer:before{content:"\e199"}.glyphicon-tree-deciduous:before{content:"\e200"}.glyphicon-cd:before{content:"\e201"}.glyphicon-save-file:before{content:"\e202"}.glyphicon-open-file:before{content:"\e203"}.glyphicon-level-up:before{content:"\e204"}.glyphicon-copy:before{content:"\e205"}.glyphicon-paste:before{content:"\e206"}.glyphicon-alert:before{content:"\e209"}.glyphicon-equalizer:before{content:"\e210"}.glyphicon-king:before{content:"\e211"}.glyphicon-queen:before{content:"\e212"}.glyphicon-pawn:before{content:"\e213"}.glyphicon-bishop:before{content:"\e214"}.glyphicon-knight:before{content:"\e215"}.glyphicon-baby-formula:before{content:"\e216"}.glyphicon-tent:before{content:"\26fa"}.glyphicon-blackboard:before{content:"\e218"}.glyphicon-bed:before{content:"\e219"}.glyphicon-apple:before{content:"\f8ff"}.glyphicon-erase:before{content:"\e221"}.glyphicon-hourglass:before{content:"\231b"}.glyphicon-lamp:before{content:"\e223"}.glyphicon-duplicate:before{content:"\e224"}.glyphicon-piggy-bank:before{content:"\e225"}.glyphicon-scissors:before{content:"\e226"}.glyphicon-bitcoin:before{content:"\e227"}.glyphicon-btc:before{content:"\e227"}.glyphicon-xbt:before{content:"\e227"}.glyphicon-yen:before{content:"\00a5"}.glyphicon-jpy:before{content:"\00a5"}.glyphicon-ruble:before{content:"\20bd"}.glyphicon-rub:before{content:"\20bd"}.glyphicon-scale:before{content:"\e230"}.glyphicon-ice-lolly:before{content:"\e231"}.glyphicon-ice-lolly-tasted:before{content:"\e232"}.glyphicon-education:before{content:"\e233"}.glyphicon-option-horizontal:before{content:"\e234"}.glyphicon-option-vertical:before{content:"\e235"}.glyphicon-menu-hamburger:before{content:"\e236"}.glyphicon-modal-window:before{content:"\e237"}.glyphicon-oil:before{content:"\e238"}.glyphicon-grain:before{content:"\e239"}.glyphicon-sunglasses:before{content:"\e240"}.glyphicon-text-size:before{content:"\e241"}.glyphicon-text-color:before{content:"\e242"}.glyphicon-text-background:before{content:"\e243"}.glyphicon-object-align-top:before{content:"\e244"}.glyphicon-object-align-bottom:before{content:"\e245"}.glyphicon-object-align-horizontal:before{content:"\e246"}.glyphicon-object-align-left:before{content:"\e247"}.glyphicon-object-align-vertical:before{content:"\e248"}.glyphicon-object-align-right:before{content:"\e249"}.glyphicon-triangle-right:before{content:"\e250"}.glyphicon-triangle-left:before{content:"\e251"}.glyphicon-triangle-bottom:before{content:"\e252"}.glyphicon-triangle-top:before{content:"\e253"}.glyphicon-console:before{content:"\e254"}.glyphicon-superscript:before{content:"\e255"}.glyphicon-subscript:before{content:"\e256"}.glyphicon-menu-left:before{content:"\e257"}.glyphicon-menu-right:before{content:"\e258"}.glyphicon-menu-down:before{content:"\e259"}.glyphicon-menu-up:before{content:"\e260"}*{-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box}:after,:before{-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box}html{font-size:10px;-webkit-tap-highlight-color:rgba(0,0,0,0)}body{font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-size:14px;line-height:1.42857143;color:#333;background-color:#fff}button,input,select,textarea{font-family:inherit;font-size:inherit;line-height:inherit}a{color:#337ab7;text-decoration:none}a:focus,a:hover{color:#23527c;text-decoration:underline}a:focus{outline:thin dotted;outline:5px auto -webkit-focus-ring-color;outline-offset:-2px}figure{margin:0}img{vertical-align:middle}.carousel-inner>.item>a>img,.carousel-inner>.item>img,.img-responsive,.thumbnail a>img,.thumbnail>img{display:block;max-width:100%;height:auto}.img-rounded{border-radius:6px}.img-thumbnail{display:inline-block;max-width:100%;height:auto;padding:4px;line-height:1.42857143;background-color:#fff;border:1px solid #ddd;border-radius:4px;-webkit-transition:all .2s ease-in-out;-o-transition:all .2s ease-in-out;transition:all .2s ease-in-out}.img-circle{border-radius:50%}hr{margin-top:20px;margin-bottom:20px;border:0;border-top:1px solid #eee}.sr-only{position:absolute;width:1px;height:1px;padding:0;margin:-1px;overflow:hidden;clip:rect(0,0,0,0);border:0}.sr-only-focusable:active,.sr-only-focusable:focus{position:static;width:auto;height:auto;margin:0;overflow:visible;clip:auto}[role=button]{cursor:pointer}.h1,.h2,.h3,.h4,.h5,.h6,h1,h2,h3,h4,h5,h6{font-family:inherit;font-weight:500;line-height:1.1;color:inherit}.h1 .small,.h1 small,.h2 .small,.h2 small,.h3 .small,.h3 small,.h4 .small,.h4 small,.h5 .small,.h5 small,.h6 .small,.h6 small,h1 .small,h1 small,h2 .small,h2 small,h3 .small,h3 small,h4 .small,h4 small,h5 .small,h5 small,h6 .small,h6 small{font-weight:400;line-height:1;color:#777}.h1,.h2,.h3,h1,h2,h3{margin-top:20px;margin-bottom:10px}.h1 .small,.h1 small,.h2 .small,.h2 small,.h3 .small,.h3 small,h1 .small,h1 small,h2 .small,h2 small,h3 .small,h3 small{font-size:65%}.h4,.h5,.h6,h4,h5,h6{margin-top:10px;margin-bottom:10px}.h4 .small,.h4 small,.h5 .small,.h5 small,.h6 .small,.h6 small,h4 .small,h4 small,h5 .small,h5 small,h6 .small,h6 small{font-size:75%}.h1,h1{font-size:36px}.h2,h2{font-size:30px}.h3,h3{font-size:24px}.h4,h4{font-size:18px}.h5,h5{font-size:14px}.h6,h6{font-size:12px}p{margin:0 0 10px}.lead{margin-bottom:20px;font-size:16px;font-weight:300;line-height:1.4}@media (min-width:768px){.lead{font-size:21px}}.small,small{font-size:85%}.mark,mark{padding:.2em;background-color:#fcf8e3}.text-left{text-align:left}.text-right{text-align:right}.text-center{text-align:center}.text-justify{text-align:justify}.text-nowrap{white-space:nowrap}.text-lowercase{text-transform:lowercase}.text-uppercase{text-transform:uppercase}.text-capitalize{text-transform:capitalize}.text-muted{color:#777}.text-primary{color:#337ab7}a.text-primary:focus,a.text-primary:hover{color:#286090}.text-success{color:#3c763d}a.text-success:focus,a.text-success:hover{color:#2b542c}.text-info{color:#31708f}a.text-info:focus,a.text-info:hover{color:#245269}.text-warning{color:#8a6d3b}a.text-warning:focus,a.text-warning:hover{color:#66512c}.text-danger{color:#a94442}a.text-danger:focus,a.text-danger:hover{color:#843534}.bg-primary{color:#fff;background-color:#337ab7}a.bg-primary:focus,a.bg-primary:hover{background-color:#286090}.bg-success{background-color:#dff0d8}a.bg-success:focus,a.bg-success:hover{background-color:#c1e2b3}.bg-info{background-color:#d9edf7}a.bg-info:focus,a.bg-info:hover{background-color:#afd9ee}.bg-warning{background-color:#fcf8e3}a.bg-warning:focus,a.bg-warning:hover{background-color:#f7ecb5}.bg-danger{background-color:#f2dede}a.bg-danger:focus,a.bg-danger:hover{background-color:#e4b9b9}.page-header{padding-bottom:9px;margin:40px 0 20px;border-bottom:1px solid #eee}ol,ul{margin-top:0;margin-bottom:10px}ol ol,ol ul,ul ol,ul ul{margin-bottom:0}.list-unstyled{padding-left:0;list-style:none}.list-inline{padding-left:0;margin-left:-5px;list-style:none}.list-inline>li{display:inline-block;padding-right:5px;padding-left:5px}dl{margin-top:0;margin-bottom:20px}dd,dt{line-height:1.42857143}dt{font-weight:700}dd{margin-left:0}@media (min-width:768px){.dl-horizontal dt{float:left;width:160px;overflow:hidden;clear:left;text-align:right;text-overflow:ellipsis;white-space:nowrap}.dl-horizontal dd{margin-left:180px}}abbr[data-original-title],abbr[title]{cursor:help;border-bottom:1px dotted #777}.initialism{font-size:90%;text-transform:uppercase}blockquote{padding:10px 20px;margin:0 0 20px;font-size:17.5px;border-left:5px solid #eee}blockquote ol:last-child,blockquote p:last-child,blockquote ul:last-child{margin-bottom:0}blockquote .small,blockquote footer,blockquote small{display:block;font-size:80%;line-height:1.42857143;color:#777}blockquote .small:before,blockquote footer:before,blockquote small:before{content:'\2014 \00A0'}.blockquote-reverse,blockquote.pull-right{padding-right:15px;padding-left:0;text-align:right;border-right:5px solid #eee;border-left:0}.blockquote-reverse .small:before,.blockquote-reverse footer:before,.blockquote-reverse small:before,blockquote.pull-right .small:before,blockquote.pull-right footer:before,blockquote.pull-right small:before{content:''}.blockquote-reverse .small:after,.blockquote-reverse footer:after,.blockquote-reverse small:after,blockquote.pull-right .small:after,blockquote.pull-right footer:after,blockquote.pull-right small:after{content:'\00A0 \2014'}address{margin-bottom:20px;font-style:normal;line-height:1.42857143}code,kbd,pre,samp{font-family:monospace}code{padding:2px 4px;font-size:90%;color:#c7254e;background-color:#f9f2f4;border-radius:4px}kbd{padding:2px 4px;font-size:90%;color:#fff;background-color:#333;border-radius:3px;-webkit-box-shadow:inset 0 -1px 0 rgba(0,0,0,.25);box-shadow:inset 0 -1px 0 rgba(0,0,0,.25)}kbd kbd{padding:0;font-size:100%;font-weight:700;-webkit-box-shadow:none;box-shadow:none}pre{display:block;padding:9.5px;margin:0 0 10px;font-size:13px;line-height:1.42857143;color:#333;word-break:break-all;word-wrap:break-word;background-color:#f5f5f5;border:1px solid #ccc;border-radius:4px}pre code{padding:0;font-size:inherit;color:inherit;white-space:pre-wrap;background-color:transparent;border-radius:0}.pre-scrollable{max-height:340px;overflow-y:scroll}.container{padding-right:15px;padding-left:15px;margin-right:auto;margin-left:auto}@media (min-width:768px){.container{width:750px}}@media (min-width:992px){.container{width:970px}}@media (min-width:1200px){.container{width:1170px}}.container-fluid{padding-right:15px;padding-left:15px;margin-right:auto;margin-left:auto}.row{margin-right:-15px;margin-left:-15px}.col-lg-1,.col-lg-10,.col-lg-11,.col-lg-12,.col-lg-2,.col-lg-3,.col-lg-4,.col-lg-5,.col-lg-6,.col-lg-7,.col-lg-8,.col-lg-9,.col-md-1,.col-md-10,.col-md-11,.col-md-12,.col-md-2,.col-md-3,.col-md-4,.col-md-5,.col-md-6,.col-md-7,.col-md-8,.col-md-9,.col-sm-1,.col-sm-10,.col-sm-11,.col-sm-12,.col-sm-2,.col-sm-3,.col-sm-4,.col-sm-5,.col-sm-6,.col-sm-7,.col-sm-8,.col-sm-9,.col-xs-1,.col-xs-10,.col-xs-11,.col-xs-12,.col-xs-2,.col-xs-3,.col-xs-4,.col-xs-5,.col-xs-6,.col-xs-7,.col-xs-8,.col-xs-9{position:relative;min-height:1px;padding-right:15px;padding-left:15px}.col-xs-1,.col-xs-10,.col-xs-11,.col-xs-12,.col-xs-2,.col-xs-3,.col-xs-4,.col-xs-5,.col-xs-6,.col-xs-7,.col-xs-8,.col-xs-9{float:left}.col-xs-12{width:100%}.col-xs-11{width:91.66666667%}.col-xs-10{width:83.33333333%}.col-xs-9{width:75%}.col-xs-8{width:66.66666667%}.col-xs-7{width:58.33333333%}.col-xs-6{width:50%}.col-xs-5{width:41.66666667%}.col-xs-4{width:33.33333333%}.col-xs-3{width:25%}.col-xs-2{width:16.66666667%}.col-xs-1{width:8.33333333%}.col-xs-pull-12{right:100%}.col-xs-pull-11{right:91.66666667%}.col-xs-pull-10{right:83.33333333%}.col-xs-pull-9{right:75%}.col-xs-pull-8{right:66.66666667%}.col-xs-pull-7{right:58.33333333%}.col-xs-pull-6{right:50%}.col-xs-pull-5{right:41.66666667%}.col-xs-pull-4{right:33.33333333%}.col-xs-pull-3{right:25%}.col-xs-pull-2{right:16.66666667%}.col-xs-pull-1{right:8.33333333%}.col-xs-pull-0{right:auto}.col-xs-push-12{left:100%}.col-xs-push-11{left:91.66666667%}.col-xs-push-10{left:83.33333333%}.col-xs-push-9{left:75%}.col-xs-push-8{left:66.66666667%}.col-xs-push-7{left:58.33333333%}.col-xs-push-6{left:50%}.col-xs-push-5{left:41.66666667%}.col-xs-push-4{left:33.33333333%}.col-xs-push-3{left:25%}.col-xs-push-2{left:16.66666667%}.col-xs-push-1{left:8.33333333%}.col-xs-push-0{left:auto}.col-xs-offset-12{margin-left:100%}.col-xs-offset-11{margin-left:91.66666667%}.col-xs-offset-10{margin-left:83.33333333%}.col-xs-offset-9{margin-left:75%}.col-xs-offset-8{margin-left:66.66666667%}.col-xs-offset-7{margin-left:58.33333333%}.col-xs-offset-6{margin-left:50%}.col-xs-offset-5{margin-left:41.66666667%}.col-xs-offset-4{margin-left:33.33333333%}.col-xs-offset-3{margin-left:25%}.col-xs-offset-2{margin-left:16.66666667%}.col-xs-offset-1{margin-left:8.33333333%}.col-xs-offset-0{margin-left:0}@media (min-width:768px){.col-sm-1,.col-sm-10,.col-sm-11,.col-sm-12,.col-sm-2,.col-sm-3,.col-sm-4,.col-sm-5,.col-sm-6,.col-sm-7,.col-sm-8,.col-sm-9{float:left}.col-sm-12{width:100%}.col-sm-11{width:91.66666667%}.col-sm-10{width:83.33333333%}.col-sm-9{width:75%}.col-sm-8{width:66.66666667%}.col-sm-7{width:58.33333333%}.col-sm-6{width:50%}.col-sm-5{width:41.66666667%}.col-sm-4{width:33.33333333%}.col-sm-3{width:25%}.col-sm-2{width:16.66666667%}.col-sm-1{width:8.33333333%}.col-sm-pull-12{right:100%}.col-sm-pull-11{right:91.66666667%}.col-sm-pull-10{right:83.33333333%}.col-sm-pull-9{right:75%}.col-sm-pull-8{right:66.66666667%}.col-sm-pull-7{right:58.33333333%}.col-sm-pull-6{right:50%}.col-sm-pull-5{right:41.66666667%}.col-sm-pull-4{right:33.33333333%}.col-sm-pull-3{right:25%}.col-sm-pull-2{right:16.66666667%}.col-sm-pull-1{right:8.33333333%}.col-sm-pull-0{right:auto}.col-sm-push-12{left:100%}.col-sm-push-11{left:91.66666667%}.col-sm-push-10{left:83.33333333%}.col-sm-push-9{left:75%}.col-sm-push-8{left:66.66666667%}.col-sm-push-7{left:58.33333333%}.col-sm-push-6{left:50%}.col-sm-push-5{left:41.66666667%}.col-sm-push-4{left:33.33333333%}.col-sm-push-3{left:25%}.col-sm-push-2{left:16.66666667%}.col-sm-push-1{left:8.33333333%}.col-sm-push-0{left:auto}.col-sm-offset-12{margin-left:100%}.col-sm-offset-11{margin-left:91.66666667%}.col-sm-offset-10{margin-left:83.33333333%}.col-sm-offset-9{margin-left:75%}.col-sm-offset-8{margin-left:66.66666667%}.col-sm-offset-7{margin-left:58.33333333%}.col-sm-offset-6{margin-left:50%}.col-sm-offset-5{margin-left:41.66666667%}.col-sm-offset-4{margin-left:33.33333333%}.col-sm-offset-3{margin-left:25%}.col-sm-offset-2{margin-left:16.66666667%}.col-sm-offset-1{margin-left:8.33333333%}.col-sm-offset-0{margin-left:0}}@media (min-width:992px){.col-md-1,.col-md-10,.col-md-11,.col-md-12,.col-md-2,.col-md-3,.col-md-4,.col-md-5,.col-md-6,.col-md-7,.col-md-8,.col-md-9{float:left}.col-md-12{width:100%}.col-md-11{width:91.66666667%}.col-md-10{width:83.33333333%}.col-md-9{width:75%}.col-md-8{width:66.66666667%}.col-md-7{width:58.33333333%}.col-md-6{width:50%}.col-md-5{width:41.66666667%}.col-md-4{width:33.33333333%}.col-md-3{width:25%}.col-md-2{width:16.66666667%}.col-md-1{width:8.33333333%}.col-md-pull-12{right:100%}.col-md-pull-11{right:91.66666667%}.col-md-pull-10{right:83.33333333%}.col-md-pull-9{right:75%}.col-md-pull-8{right:66.66666667%}.col-md-pull-7{right:58.33333333%}.col-md-pull-6{right:50%}.col-md-pull-5{right:41.66666667%}.col-md-pull-4{right:33.33333333%}.col-md-pull-3{right:25%}.col-md-pull-2{right:16.66666667%}.col-md-pull-1{right:8.33333333%}.col-md-pull-0{right:auto}.col-md-push-12{left:100%}.col-md-push-11{left:91.66666667%}.col-md-push-10{left:83.33333333%}.col-md-push-9{left:75%}.col-md-push-8{left:66.66666667%}.col-md-push-7{left:58.33333333%}.col-md-push-6{left:50%}.col-md-push-5{left:41.66666667%}.col-md-push-4{left:33.33333333%}.col-md-push-3{left:25%}.col-md-push-2{left:16.66666667%}.col-md-push-1{left:8.33333333%}.col-md-push-0{left:auto}.col-md-offset-12{margin-left:100%}.col-md-offset-11{margin-left:91.66666667%}.col-md-offset-10{margin-left:83.33333333%}.col-md-offset-9{margin-left:75%}.col-md-offset-8{margin-left:66.66666667%}.col-md-offset-7{margin-left:58.33333333%}.col-md-offset-6{margin-left:50%}.col-md-offset-5{margin-left:41.66666667%}.col-md-offset-4{margin-left:33.33333333%}.col-md-offset-3{margin-left:25%}.col-md-offset-2{margin-left:16.66666667%}.col-md-offset-1{margin-left:8.33333333%}.col-md-offset-0{margin-left:0}}@media (min-width:1200px){.col-lg-1,.col-lg-10,.col-lg-11,.col-lg-12,.col-lg-2,.col-lg-3,.col-lg-4,.col-lg-5,.col-lg-6,.col-lg-7,.col-lg-8,.col-lg-9{float:left}.col-lg-12{width:100%}.col-lg-11{width:91.66666667%}.col-lg-10{width:83.33333333%}.col-lg-9{width:75%}.col-lg-8{width:66.66666667%}.col-lg-7{width:58.33333333%}.col-lg-6{width:50%}.col-lg-5{width:41.66666667%}.col-lg-4{width:33.33333333%}.col-lg-3{width:25%}.col-lg-2{width:16.66666667%}.col-lg-1{width:8.33333333%}.col-lg-pull-12{right:100%}.col-lg-pull-11{right:91.66666667%}.col-lg-pull-10{right:83.33333333%}.col-lg-pull-9{right:75%}.col-lg-pull-8{right:66.66666667%}.col-lg-pull-7{right:58.33333333%}.col-lg-pull-6{right:50%}.col-lg-pull-5{right:41.66666667%}.col-lg-pull-4{right:33.33333333%}.col-lg-pull-3{right:25%}.col-lg-pull-2{right:16.66666667%}.col-lg-pull-1{right:8.33333333%}.col-lg-pull-0{right:auto}.col-lg-push-12{left:100%}.col-lg-push-11{left:91.66666667%}.col-lg-push-10{left:83.33333333%}.col-lg-push-9{left:75%}.col-lg-push-8{left:66.66666667%}.col-lg-push-7{left:58.33333333%}.col-lg-push-6{left:50%}.col-lg-push-5{left:41.66666667%}.col-lg-push-4{left:33.33333333%}.col-lg-push-3{left:25%}.col-lg-push-2{left:16.66666667%}.col-lg-push-1{left:8.33333333%}.col-lg-push-0{left:auto}.col-lg-offset-12{margin-left:100%}.col-lg-offset-11{margin-left:91.66666667%}.col-lg-offset-10{margin-left:83.33333333%}.col-lg-offset-9{margin-left:75%}.col-lg-offset-8{margin-left:66.66666667%}.col-lg-offset-7{margin-left:58.33333333%}.col-lg-offset-6{margin-left:50%}.col-lg-offset-5{margin-left:41.66666667%}.col-lg-offset-4{margin-left:33.33333333%}.col-lg-offset-3{margin-left:25%}.col-lg-offset-2{margin-left:16.66666667%}.col-lg-offset-1{margin-left:8.33333333%}.col-lg-offset-0{margin-left:0}}table{background-color:transparent}caption{padding-top:8px;padding-bottom:8px;color:#777;text-align:left}th{}.table{width:100%;max-width:100%;margin-bottom:20px}.table>tbody>tr>td,.table>tbody>tr>th,.table>tfoot>tr>td,.table>tfoot>tr>th,.table>thead>tr>td,.table>thead>tr>th{padding:8px;line-height:1.42857143;vertical-align:top;border-top:1px solid #ddd}.table>thead>tr>th{vertical-align:bottom;border-bottom:2px solid #ddd}.table>caption+thead>tr:first-child>td,.table>caption+thead>tr:first-child>th,.table>colgroup+thead>tr:first-child>td,.table>colgroup+thead>tr:first-child>th,.table>thead:first-child>tr:first-child>td,.table>thead:first-child>tr:first-child>th{border-top:0}.table>tbody+tbody{border-top:2px solid #ddd}.table .table{background-color:#fff}.table-condensed>tbody>tr>td,.table-condensed>tbody>tr>th,.table-condensed>tfoot>tr>td,.table-condensed>tfoot>tr>th,.table-condensed>thead>tr>td,.table-condensed>thead>tr>th{padding:5px}.table-bordered{border:1px solid #ddd}.table-bordered>tbody>tr>td,.table-bordered>tbody>tr>th,.table-bordered>tfoot>tr>td,.table-bordered>tfoot>tr>th,.table-bordered>thead>tr>td,.table-bordered>thead>tr>th{border:1px solid #ddd}.table-bordered>thead>tr>td,.table-bordered>thead>tr>th{border-bottom-width:2px}.table-striped>tbody>tr:nth-of-type(odd){background-color:#f9f9f9}.table-hover>tbody>tr:hover{background-color:#f5f5f5}table col[class*=col-]{position:static;display:table-column;float:none}table td[class*=col-],table th[class*=col-]{position:static;display:table-cell;float:none}.table>tbody>tr.active>td,.table>tbody>tr.active>th,.table>tbody>tr>td.active,.table>tbody>tr>th.active,.table>tfoot>tr.active>td,.table>tfoot>tr.active>th,.table>tfoot>tr>td.active,.table>tfoot>tr>th.active,.table>thead>tr.active>td,.table>thead>tr.active>th,.table>thead>tr>td.active,.table>thead>tr>th.active{background-color:#f5f5f5}.table-hover>tbody>tr.active:hover>td,.table-hover>tbody>tr.active:hover>th,.table-hover>tbody>tr:hover>.active,.table-hover>tbody>tr>td.active:hover,.table-hover>tbody>tr>th.active:hover{background-color:#e8e8e8}.table>tbody>tr.success>td,.table>tbody>tr.success>th,.table>tbody>tr>td.success,.table>tbody>tr>th.success,.table>tfoot>tr.success>td,.table>tfoot>tr.success>th,.table>tfoot>tr>td.success,.table>tfoot>tr>th.success,.table>thead>tr.success>td,.table>thead>tr.success>th,.table>thead>tr>td.success,.table>thead>tr>th.success{background-color:#dff0d8}.table-hover>tbody>tr.success:hover>td,.table-hover>tbody>tr.success:hover>th,.table-hover>tbody>tr:hover>.success,.table-hover>tbody>tr>td.success:hover,.table-hover>tbody>tr>th.success:hover{background-color:#d0e9c6}.table>tbody>tr.info>td,.table>tbody>tr.info>th,.table>tbody>tr>td.info,.table>tbody>tr>th.info,.table>tfoot>tr.info>td,.table>tfoot>tr.info>th,.table>tfoot>tr>td.info,.table>tfoot>tr>th.info,.table>thead>tr.info>td,.table>thead>tr.info>th,.table>thead>tr>td.info,.table>thead>tr>th.info{background-color:#d9edf7}.table-hover>tbody>tr.info:hover>td,.table-hover>tbody>tr.info:hover>th,.table-hover>tbody>tr:hover>.info,.table-hover>tbody>tr>td.info:hover,.table-hover>tbody>tr>th.info:hover{background-color:#c4e3f3}.table>tbody>tr.warning>td,.table>tbody>tr.warning>th,.table>tbody>tr>td.warning,.table>tbody>tr>th.warning,.table>tfoot>tr.warning>td,.table>tfoot>tr.warning>th,.table>tfoot>tr>td.warning,.table>tfoot>tr>th.warning,.table>thead>tr.warning>td,.table>thead>tr.warning>th,.table>thead>tr>td.warning,.table>thead>tr>th.warning{background-color:#fcf8e3}.table-hover>tbody>tr.warning:hover>td,.table-hover>tbody>tr.warning:hover>th,.table-hover>tbody>tr:hover>.warning,.table-hover>tbody>tr>td.warning:hover,.table-hover>tbody>tr>th.warning:hover{background-color:#faf2cc}.table>tbody>tr.danger>td,.table>tbody>tr.danger>th,.table>tbody>tr>td.danger,.table>tbody>tr>th.danger,.table>tfoot>tr.danger>td,.table>tfoot>tr.danger>th,.table>tfoot>tr>td.danger,.table>tfoot>tr>th.danger,.table>thead>tr.danger>td,.table>thead>tr.danger>th,.table>thead>tr>td.danger,.table>thead>tr>th.danger{background-color:#f2dede}.table-hover>tbody>tr.danger:hover>td,.table-hover>tbody>tr.danger:hover>th,.table-hover>tbody>tr:hover>.danger,.table-hover>tbody>tr>td.danger:hover,.table-hover>tbody>tr>th.danger:hover{background-color:#ebcccc}.table-responsive{min-height:.01%;overflow-x:auto}@media screen and (max-width:767px){.table-responsive{width:100%;margin-bottom:15px;overflow-y:hidden;-ms-overflow-style:-ms-autohiding-scrollbar;border:1px solid #ddd}.table-responsive>.table{margin-bottom:0}.table-responsive>.table>tbody>tr>td,.table-responsive>.table>tbody>tr>th,.table-responsive>.table>tfoot>tr>td,.table-responsive>.table>tfoot>tr>th,.table-responsive>.table>thead>tr>td,.table-responsive>.table>thead>tr>th{white-space:nowrap}.table-responsive>.table-bordered{border:0}.table-responsive>.table-bordered>tbody>tr>td:first-child,.table-responsive>.table-bordered>tbody>tr>th:first-child,.table-responsive>.table-bordered>tfoot>tr>td:first-child,.table-responsive>.table-bordered>tfoot>tr>th:first-child,.table-responsive>.table-bordered>thead>tr>td:first-child,.table-responsive>.table-bordered>thead>tr>th:first-child{border-left:0}.table-responsive>.table-bordered>tbody>tr>td:last-child,.table-responsive>.table-bordered>tbody>tr>th:last-child,.table-responsive>.table-bordered>tfoot>tr>td:last-child,.table-responsive>.table-bordered>tfoot>tr>th:last-child,.table-responsive>.table-bordered>thead>tr>td:last-child,.table-responsive>.table-bordered>thead>tr>th:last-child{border-right:0}.table-responsive>.table-bordered>tbody>tr:last-child>td,.table-responsive>.table-bordered>tbody>tr:last-child>th,.table-responsive>.table-bordered>tfoot>tr:last-child>td,.table-responsive>.table-bordered>tfoot>tr:last-child>th{border-bottom:0}}fieldset{min-width:0;padding:0;margin:0;border:0}legend{display:block;width:100%;padding:0;margin-bottom:20px;font-size:21px;line-height:inherit;color:#333;border:0;border-bottom:1px solid #e5e5e5}label{display:inline-block;max-width:100%;margin-bottom:5px;font-weight:700}input[type=search]{-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box}input[type=checkbox],input[type=radio]{margin:4px 0 0;margin-top:1px\9;line-height:normal}input[type=file]{display:block}input[type=range]{display:block;width:100%}select[multiple],select[size]{height:auto}input[type=file]:focus,input[type=checkbox]:focus,input[type=radio]:focus{outline:thin dotted;outline:5px auto -webkit-focus-ring-color;outline-offset:-2px}output{display:block;padding-top:7px;font-size:14px;line-height:1.42857143;color:#555}.form-control{display:block;width:100%;height:34px;padding:6px 12px;font-size:14px;line-height:1.42857143;color:#555;background-color:#fff;background-image:none;border:1px solid #ccc;border-radius:4px;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,.075);box-shadow:inset 0 1px 1px rgba(0,0,0,.075);-webkit-transition:border-color ease-in-out .15s,-webkit-box-shadow ease-in-out .15s;-o-transition:border-color ease-in-out .15s,box-shadow ease-in-out .15s;transition:border-color ease-in-out .15s,box-shadow ease-in-out .15s}.form-control:focus{border-color:#66afe9;outline:0;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,.075),0 0 8px rgba(102,175,233,.6);box-shadow:inset 0 1px 1px rgba(0,0,0,.075),0 0 8px rgba(102,175,233,.6)}.form-control::-moz-placeholder{color:#999;opacity:1}.form-control:-ms-input-placeholder{color:#999}.form-control::-webkit-input-placeholder{color:#999}.form-control[disabled],.form-control[readonly],fieldset[disabled] .form-control{background-color:#eee;opacity:1}.form-control[disabled],fieldset[disabled] .form-control{cursor:not-allowed}textarea.form-control{height:auto}input[type=search]{-webkit-appearance:none}@media screen and (-webkit-min-device-pixel-ratio:0){input[type=date].form-control,input[type=time].form-control,input[type=datetime-local].form-control,input[type=month].form-control{line-height:34px}.input-group-sm input[type=date],.input-group-sm input[type=time],.input-group-sm input[type=datetime-local],.input-group-sm input[type=month],input[type=date].input-sm,input[type=time].input-sm,input[type=datetime-local].input-sm,input[type=month].input-sm{line-height:30px}.input-group-lg input[type=date],.input-group-lg input[type=time],.input-group-lg input[type=datetime-local],.input-group-lg input[type=month],input[type=date].input-lg,input[type=time].input-lg,input[type=datetime-local].input-lg,input[type=month].input-lg{line-height:46px}}.form-group{margin-bottom:15px}.checkbox,.radio{position:relative;display:block;margin-top:10px;margin-bottom:10px}.checkbox label,.radio label{min-height:20px;padding-left:20px;margin-bottom:0;font-weight:400;cursor:pointer}.checkbox input[type=checkbox],.checkbox-inline input[type=checkbox],.radio input[type=radio],.radio-inline input[type=radio]{position:absolute;margin-top:4px\9;margin-left:-20px}.checkbox+.checkbox,.radio+.radio{margin-top:-5px}.checkbox-inline,.radio-inline{position:relative;display:inline-block;padding-left:20px;margin-bottom:0;font-weight:400;vertical-align:middle;cursor:pointer}.checkbox-inline+.checkbox-inline,.radio-inline+.radio-inline{margin-top:0;margin-left:10px}fieldset[disabled] input[type=checkbox],fieldset[disabled] input[type=radio],input[type=checkbox].disabled,input[type=checkbox][disabled],input[type=radio].disabled,input[type=radio][disabled]{cursor:not-allowed}.checkbox-inline.disabled,.radio-inline.disabled,fieldset[disabled] .checkbox-inline,fieldset[disabled] .radio-inline{cursor:not-allowed}.checkbox.disabled label,.radio.disabled label,fieldset[disabled] .checkbox label,fieldset[disabled] .radio label{cursor:not-allowed}.form-control-static{min-height:34px;padding-top:7px;padding-bottom:7px;margin-bottom:0}.form-control-static.input-lg,.form-control-static.input-sm{padding-right:0;padding-left:0}.input-sm{height:30px;padding:5px 10px;font-size:12px;line-height:1.5;border-radius:3px}select.input-sm{height:30px;line-height:30px}select[multiple].input-sm,textarea.input-sm{height:auto}.form-group-sm .form-control{height:30px;padding:5px 10px;font-size:12px;line-height:1.5;border-radius:3px}.form-group-sm select.form-control{height:30px;line-height:30px}.form-group-sm select[multiple].form-control,.form-group-sm textarea.form-control{height:auto}.form-group-sm .form-control-static{height:30px;min-height:32px;padding:6px 10px;font-size:12px;line-height:1.5}.input-lg{height:46px;padding:10px 16px;font-size:18px;line-height:1.3333333;border-radius:6px}select.input-lg{height:46px;line-height:46px}select[multiple].input-lg,textarea.input-lg{height:auto}.form-group-lg .form-control{height:46px;padding:10px 16px;font-size:18px;line-height:1.3333333;border-radius:6px}.form-group-lg select.form-control{height:46px;line-height:46px}.form-group-lg select[multiple].form-control,.form-group-lg textarea.form-control{height:auto}.form-group-lg .form-control-static{height:46px;min-height:38px;padding:11px 16px;font-size:18px;line-height:1.3333333}.has-feedback{position:relative}.has-feedback .form-control{padding-right:42.5px}.form-control-feedback{position:absolute;top:0;right:0;z-index:2;display:block;width:34px;height:34px;line-height:34px;text-align:center;pointer-events:none}.form-group-lg .form-control+.form-control-feedback,.input-group-lg+.form-control-feedback,.input-lg+.form-control-feedback{width:46px;height:46px;line-height:46px}.form-group-sm .form-control+.form-control-feedback,.input-group-sm+.form-control-feedback,.input-sm+.form-control-feedback{width:30px;height:30px;line-height:30px}.has-success .checkbox,.has-success .checkbox-inline,.has-success .control-label,.has-success .help-block,.has-success .radio,.has-success .radio-inline,.has-success.checkbox label,.has-success.checkbox-inline label,.has-success.radio label,.has-success.radio-inline label{color:#3c763d}.has-success .form-control{border-color:#3c763d;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,.075);box-shadow:inset 0 1px 1px rgba(0,0,0,.075)}.has-success .form-control:focus{border-color:#2b542c;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,.075),0 0 6px #67b168;box-shadow:inset 0 1px 1px rgba(0,0,0,.075),0 0 6px #67b168}.has-success .input-group-addon{color:#3c763d;background-color:#dff0d8;border-color:#3c763d}.has-success .form-control-feedback{color:#3c763d}.has-warning .checkbox,.has-warning .checkbox-inline,.has-warning .control-label,.has-warning .help-block,.has-warning .radio,.has-warning .radio-inline,.has-warning.checkbox label,.has-warning.checkbox-inline label,.has-warning.radio label,.has-warning.radio-inline label{color:#8a6d3b}.has-warning .form-control{border-color:#8a6d3b;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,.075);box-shadow:inset 0 1px 1px rgba(0,0,0,.075)}.has-warning .form-control:focus{border-color:#66512c;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,.075),0 0 6px #c0a16b;box-shadow:inset 0 1px 1px rgba(0,0,0,.075),0 0 6px #c0a16b}.has-warning .input-group-addon{color:#8a6d3b;background-color:#fcf8e3;border-color:#8a6d3b}.has-warning .form-control-feedback{color:#8a6d3b}.has-error .checkbox,.has-error .checkbox-inline,.has-error .control-label,.has-error .help-block,.has-error .radio,.has-error .radio-inline,.has-error.checkbox label,.has-error.checkbox-inline label,.has-error.radio label,.has-error.radio-inline label{color:#a94442}.has-error .form-control{border-color:#a94442;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,.075);box-shadow:inset 0 1px 1px rgba(0,0,0,.075)}.has-error .form-control:focus{border-color:#843534;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,.075),0 0 6px #ce8483;box-shadow:inset 0 1px 1px rgba(0,0,0,.075),0 0 6px #ce8483}.has-error .input-group-addon{color:#a94442;background-color:#f2dede;border-color:#a94442}.has-error .form-control-feedback{color:#a94442}.has-feedback label~.form-control-feedback{top:25px}.has-feedback label.sr-only~.form-control-feedback{top:0}.help-block{display:block;margin-top:5px;margin-bottom:10px;color:#737373}@media (min-width:768px){.form-inline .form-group{display:inline-block;margin-bottom:0;vertical-align:middle}.form-inline .form-control{display:inline-block;width:auto;vertical-align:middle}.form-inline .form-control-static{display:inline-block}.form-inline .input-group{display:inline-table;vertical-align:middle}.form-inline .input-group .form-control,.form-inline .input-group .input-group-addon,.form-inline .input-group .input-group-btn{width:auto}.form-inline .input-group>.form-control{width:100%}.form-inline .control-label{margin-bottom:0;vertical-align:middle}.form-inline .checkbox,.form-inline .radio{display:inline-block;margin-top:0;margin-bottom:0;vertical-align:middle}.form-inline .checkbox label,.form-inline .radio label{padding-left:0}.form-inline .checkbox input[type=checkbox],.form-inline .radio input[type=radio]{position:relative;margin-left:0}.form-inline .has-feedback .form-control-feedback{top:0}}.form-horizontal .checkbox,.form-horizontal .checkbox-inline,.form-horizontal .radio,.form-horizontal .radio-inline{padding-top:7px;margin-top:0;margin-bottom:0}.form-horizontal .checkbox,.form-horizontal .radio{min-height:27px}.form-horizontal .form-group{margin-right:-15px;margin-left:-15px}@media (min-width:768px){.form-horizontal .control-label{padding-top:7px;margin-bottom:0;text-align:right}}.form-horizontal .has-feedback .form-control-feedback{right:15px}@media (min-width:768px){.form-horizontal .form-group-lg .control-label{padding-top:14.33px;font-size:18px}}@media (min-width:768px){.form-horizontal .form-group-sm .control-label{padding-top:6px;font-size:12px}}.btn{display:inline-block;padding:6px 12px;margin-bottom:0;font-size:14px;font-weight:400;line-height:1.42857143;text-align:center;white-space:nowrap;vertical-align:middle;-ms-touch-action:manipulation;touch-action:manipulation;cursor:pointer;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none;background-image:none;border:1px solid transparent;border-radius:4px}.btn.active.focus,.btn.active:focus,.btn.focus,.btn:active.focus,.btn:active:focus,.btn:focus{outline:thin dotted;outline:5px auto -webkit-focus-ring-color;outline-offset:-2px}.btn.focus,.btn:focus,.btn:hover{color:#333;text-decoration:none}.btn.active,.btn:active{background-image:none;outline:0;-webkit-box-shadow:inset 0 3px 5px rgba(0,0,0,.125);box-shadow:inset 0 3px 5px rgba(0,0,0,.125)}.btn.disabled,.btn[disabled],fieldset[disabled] .btn{cursor:not-allowed;filter:alpha(opacity=65);-webkit-box-shadow:none;box-shadow:none;opacity:.65}a.btn.disabled,fieldset[disabled] a.btn{pointer-events:none}.btn-default{color:#333;background-color:#fff;border-color:#ccc}.btn-default.focus,.btn-default:focus{color:#333;background-color:#e6e6e6;border-color:#8c8c8c}.btn-default:hover{color:#333;background-color:#e6e6e6;border-color:#adadad}.btn-default.active,.btn-default:active,.open>.dropdown-toggle.btn-default{color:#333;background-color:#e6e6e6;border-color:#adadad}.btn-default.active.focus,.btn-default.active:focus,.btn-default.active:hover,.btn-default:active.focus,.btn-default:active:focus,.btn-default:active:hover,.open>.dropdown-toggle.btn-default.focus,.open>.dropdown-toggle.btn-default:focus,.open>.dropdown-toggle.btn-default:hover{color:#333;background-color:#d4d4d4;border-color:#8c8c8c}.btn-default.active,.btn-default:active,.open>.dropdown-toggle.btn-default{background-image:none}.btn-default.disabled,.btn-default.disabled.active,.btn-default.disabled.focus,.btn-default.disabled:active,.btn-default.disabled:focus,.btn-default.disabled:hover,.btn-default[disabled],.btn-default[disabled].active,.btn-default[disabled].focus,.btn-default[disabled]:active,.btn-default[disabled]:focus,.btn-default[disabled]:hover,fieldset[disabled] .btn-default,fieldset[disabled] .btn-default.active,fieldset[disabled] .btn-default.focus,fieldset[disabled] .btn-default:active,fieldset[disabled] .btn-default:focus,fieldset[disabled] .btn-default:hover{background-color:#fff;border-color:#ccc}.btn-default .badge{color:#fff;background-color:#333}.btn-primary{color:#fff;background-color:#337ab7;border-color:#2e6da4}.btn-primary.focus,.btn-primary:focus{color:#fff;background-color:#286090;border-color:#122b40}.btn-primary:hover{color:#fff;background-color:#286090;border-color:#204d74}.btn-primary.active,.btn-primary:active,.open>.dropdown-toggle.btn-primary{color:#fff;background-color:#286090;border-color:#204d74}.btn-primary.active.focus,.btn-primary.active:focus,.btn-primary.active:hover,.btn-primary:active.focus,.btn-primary:active:focus,.btn-primary:active:hover,.open>.dropdown-toggle.btn-primary.focus,.open>.dropdown-toggle.btn-primary:focus,.open>.dropdown-toggle.btn-primary:hover{color:#fff;background-color:#204d74;border-color:#122b40}.btn-primary.active,.btn-primary:active,.open>.dropdown-toggle.btn-primary{background-image:none}.btn-primary.disabled,.btn-primary.disabled.active,.btn-primary.disabled.focus,.btn-primary.disabled:active,.btn-primary.disabled:focus,.btn-primary.disabled:hover,.btn-primary[disabled],.btn-primary[disabled].active,.btn-primary[disabled].focus,.btn-primary[disabled]:active,.btn-primary[disabled]:focus,.btn-primary[disabled]:hover,fieldset[disabled] .btn-primary,fieldset[disabled] .btn-primary.active,fieldset[disabled] .btn-primary.focus,fieldset[disabled] .btn-primary:active,fieldset[disabled] .btn-primary:focus,fieldset[disabled] .btn-primary:hover{background-color:#337ab7;border-color:#2e6da4}.btn-primary .badge{color:#337ab7;background-color:#fff}.btn-success{color:#fff;background-color:#5cb85c;border-color:#4cae4c}.btn-success.focus,.btn-success:focus{color:#fff;background-color:#449d44;border-color:#255625}.btn-success:hover{color:#fff;background-color:#449d44;border-color:#398439}.btn-success.active,.btn-success:active,.open>.dropdown-toggle.btn-success{color:#fff;background-color:#449d44;border-color:#398439}.btn-success.active.focus,.btn-success.active:focus,.btn-success.active:hover,.btn-success:active.focus,.btn-success:active:focus,.btn-success:active:hover,.open>.dropdown-toggle.btn-success.focus,.open>.dropdown-toggle.btn-success:focus,.open>.dropdown-toggle.btn-success:hover{color:#fff;background-color:#398439;border-color:#255625}.btn-success.active,.btn-success:active,.open>.dropdown-toggle.btn-success{background-image:none}.btn-success.disabled,.btn-success.disabled.active,.btn-success.disabled.focus,.btn-success.disabled:active,.btn-success.disabled:focus,.btn-success.disabled:hover,.btn-success[disabled],.btn-success[disabled].active,.btn-success[disabled].focus,.btn-success[disabled]:active,.btn-success[disabled]:focus,.btn-success[disabled]:hover,fieldset[disabled] .btn-success,fieldset[disabled] .btn-success.active,fieldset[disabled] .btn-success.focus,fieldset[disabled] .btn-success:active,fieldset[disabled] .btn-success:focus,fieldset[disabled] .btn-success:hover{background-color:#5cb85c;border-color:#4cae4c}.btn-success .badge{color:#5cb85c;background-color:#fff}.btn-info{color:#fff;background-color:#5bc0de;border-color:#46b8da}.btn-info.focus,.btn-info:focus{color:#fff;background-color:#31b0d5;border-color:#1b6d85}.btn-info:hover{color:#fff;background-color:#31b0d5;border-color:#269abc}.btn-info.active,.btn-info:active,.open>.dropdown-toggle.btn-info{color:#fff;background-color:#31b0d5;border-color:#269abc}.btn-info.active.focus,.btn-info.active:focus,.btn-info.active:hover,.btn-info:active.focus,.btn-info:active:focus,.btn-info:active:hover,.open>.dropdown-toggle.btn-info.focus,.open>.dropdown-toggle.btn-info:focus,.open>.dropdown-toggle.btn-info:hover{color:#fff;background-color:#269abc;border-color:#1b6d85}.btn-info.active,.btn-info:active,.open>.dropdown-toggle.btn-info{background-image:none}.btn-info.disabled,.btn-info.disabled.active,.btn-info.disabled.focus,.btn-info.disabled:active,.btn-info.disabled:focus,.btn-info.disabled:hover,.btn-info[disabled],.btn-info[disabled].active,.btn-info[disabled].focus,.btn-info[disabled]:active,.btn-info[disabled]:focus,.btn-info[disabled]:hover,fieldset[disabled] .btn-info,fieldset[disabled] .btn-info.active,fieldset[disabled] .btn-info.focus,fieldset[disabled] .btn-info:active,fieldset[disabled] .btn-info:focus,fieldset[disabled] .btn-info:hover{background-color:#5bc0de;border-color:#46b8da}.btn-info .badge{color:#5bc0de;background-color:#fff}.btn-warning{color:#fff;background-color:#f0ad4e;border-color:#eea236}.btn-warning.focus,.btn-warning:focus{color:#fff;background-color:#ec971f;border-color:#985f0d}.btn-warning:hover{color:#fff;background-color:#ec971f;border-color:#d58512}.btn-warning.active,.btn-warning:active,.open>.dropdown-toggle.btn-warning{color:#fff;background-color:#ec971f;border-color:#d58512}.btn-warning.active.focus,.btn-warning.active:focus,.btn-warning.active:hover,.btn-warning:active.focus,.btn-warning:active:focus,.btn-warning:active:hover,.open>.dropdown-toggle.btn-warning.focus,.open>.dropdown-toggle.btn-warning:focus,.open>.dropdown-toggle.btn-warning:hover{color:#fff;background-color:#d58512;border-color:#985f0d}.btn-warning.active,.btn-warning:active,.open>.dropdown-toggle.btn-warning{background-image:none}.btn-warning.disabled,.btn-warning.disabled.active,.btn-warning.disabled.focus,.btn-warning.disabled:active,.btn-warning.disabled:focus,.btn-warning.disabled:hover,.btn-warning[disabled],.btn-warning[disabled].active,.btn-warning[disabled].focus,.btn-warning[disabled]:active,.btn-warning[disabled]:focus,.btn-warning[disabled]:hover,fieldset[disabled] .btn-warning,fieldset[disabled] .btn-warning.active,fieldset[disabled] .btn-warning.focus,fieldset[disabled] .btn-warning:active,fieldset[disabled] .btn-warning:focus,fieldset[disabled] .btn-warning:hover{background-color:#f0ad4e;border-color:#eea236}.btn-warning .badge{color:#f0ad4e;background-color:#fff}.btn-danger{color:#fff;background-color:#d9534f;border-color:#d43f3a}.btn-danger.focus,.btn-danger:focus{color:#fff;background-color:#c9302c;border-color:#761c19}.btn-danger:hover{color:#fff;background-color:#c9302c;border-color:#ac2925}.btn-danger.active,.btn-danger:active,.open>.dropdown-toggle.btn-danger{color:#fff;background-color:#c9302c;border-color:#ac2925}.btn-danger.active.focus,.btn-danger.active:focus,.btn-danger.active:hover,.btn-danger:active.focus,.btn-danger:active:focus,.btn-danger:active:hover,.open>.dropdown-toggle.btn-danger.focus,.open>.dropdown-toggle.btn-danger:focus,.open>.dropdown-toggle.btn-danger:hover{color:#fff;background-color:#ac2925;border-color:#761c19}.btn-danger.active,.btn-danger:active,.open>.dropdown-toggle.btn-danger{background-image:none}.btn-danger.disabled,.btn-danger.disabled.active,.btn-danger.disabled.focus,.btn-danger.disabled:active,.btn-danger.disabled:focus,.btn-danger.disabled:hover,.btn-danger[disabled],.btn-danger[disabled].active,.btn-danger[disabled].focus,.btn-danger[disabled]:active,.btn-danger[disabled]:focus,.btn-danger[disabled]:hover,fieldset[disabled] .btn-danger,fieldset[disabled] .btn-danger.active,fieldset[disabled] .btn-danger.focus,fieldset[disabled] .btn-danger:active,fieldset[disabled] .btn-danger:focus,fieldset[disabled] .btn-danger:hover{background-color:#d9534f;border-color:#d43f3a}.btn-danger .badge{color:#d9534f;background-color:#fff}.btn-link{font-weight:400;color:#337ab7;border-radius:0}.btn-link,.btn-link.active,.btn-link:active,.btn-link[disabled],fieldset[disabled] .btn-link{background-color:transparent;-webkit-box-shadow:none;box-shadow:none}.btn-link,.btn-link:active,.btn-link:focus,.btn-link:hover{border-color:transparent}.btn-link:focus,.btn-link:hover{color:#23527c;text-decoration:underline;background-color:transparent}.btn-link[disabled]:focus,.btn-link[disabled]:hover,fieldset[disabled] .btn-link:focus,fieldset[disabled] .btn-link:hover{color:#777;text-decoration:none}.btn-group-lg>.btn,.btn-lg{padding:10px 16px;font-size:18px;line-height:1.3333333;border-radius:6px}.btn-group-sm>.btn,.btn-sm{padding:5px 10px;font-size:12px;line-height:1.5;border-radius:3px}.btn-group-xs>.btn,.btn-xs{padding:1px 5px;font-size:12px;line-height:1.5;border-radius:3px}.btn-block{display:block;width:100%}.btn-block+.btn-block{margin-top:5px}input[type=button].btn-block,input[type=reset].btn-block,input[type=submit].btn-block{width:100%}.fade{opacity:0;-webkit-transition:opacity .15s linear;-o-transition:opacity .15s linear;transition:opacity .15s linear}.fade.in{opacity:1}.collapse{display:none}.collapse.in{display:block}tr.collapse.in{display:table-row}tbody.collapse.in{display:table-row-group}.collapsing{position:relative;height:0;overflow:hidden;-webkit-transition-timing-function:ease;-o-transition-timing-function:ease;transition-timing-function:ease;-webkit-transition-duration:.35s;-o-transition-duration:.35s;transition-duration:.35s;-webkit-transition-property:height,visibility;-o-transition-property:height,visibility;transition-property:height,visibility}.caret{display:inline-block;width:0;height:0;margin-left:2px;vertical-align:middle;border-top:4px dashed;border-top:4px solid\9;border-right:4px solid transparent;border-left:4px solid transparent}.dropdown,.dropup{position:relative}.dropdown-toggle:focus{outline:0}.dropdown-menu{position:absolute;top:100%;left:0;z-index:1000;display:none;float:left;min-width:160px;padding:5px 0;margin:2px 0 0;font-size:14px;text-align:left;list-style:none;background-color:#fff;-webkit-background-clip:padding-box;background-clip:padding-box;border:1px solid #ccc;border:1px solid rgba(0,0,0,.15);border-radius:4px;-webkit-box-shadow:0 6px 12px rgba(0,0,0,.175);box-shadow:0 6px 12px rgba(0,0,0,.175)}.dropdown-menu.pull-right{right:0;left:auto}.dropdown-menu .divider{height:1px;margin:9px 0;overflow:hidden;background-color:#e5e5e5}.dropdown-menu>li>a{display:block;padding:3px 20px;clear:both;font-weight:400;line-height:1.42857143;color:#333;white-space:nowrap}.dropdown-menu>li>a:focus,.dropdown-menu>li>a:hover{color:#262626;text-decoration:none;background-color:#f5f5f5}.dropdown-menu>.active>a,.dropdown-menu>.active>a:focus,.dropdown-menu>.active>a:hover{color:#fff;text-decoration:none;background-color:#337ab7;outline:0}.dropdown-menu>.disabled>a,.dropdown-menu>.disabled>a:focus,.dropdown-menu>.disabled>a:hover{color:#777}.dropdown-menu>.disabled>a:focus,.dropdown-menu>.disabled>a:hover{text-decoration:none;cursor:not-allowed;background-color:transparent;background-image:none;filter:progid:DXImageTransform.Microsoft.gradient(enabled=false)}.open>.dropdown-menu{display:block}.open>a{outline:0}.dropdown-menu-right{right:0;left:auto}.dropdown-menu-left{right:auto;left:0}.dropdown-header{display:block;padding:3px 20px;font-size:12px;line-height:1.42857143;color:#777;white-space:nowrap}.dropdown-backdrop{position:fixed;top:0;right:0;bottom:0;left:0;z-index:990}.pull-right>.dropdown-menu{right:0;left:auto}.dropup .caret,.navbar-fixed-bottom .dropdown .caret{content:"";border-top:0;border-bottom:4px dashed;border-bottom:4px solid\9}.dropup .dropdown-menu,.navbar-fixed-bottom .dropdown .dropdown-menu{top:auto;bottom:100%;margin-bottom:2px}@media (min-width:768px){.navbar-right .dropdown-menu{right:0;left:auto}.navbar-right .dropdown-menu-left{right:auto;left:0}}.btn-group,.btn-group-vertical{position:relative;display:inline-block;vertical-align:middle}.btn-group-vertical>.btn,.btn-group>.btn{position:relative;float:left}.btn-group-vertical>.btn.active,.btn-group-vertical>.btn:active,.btn-group-vertical>.btn:focus,.btn-group-vertical>.btn:hover,.btn-group>.btn.active,.btn-group>.btn:active,.btn-group>.btn:focus,.btn-group>.btn:hover{z-index:2}.btn-group .btn+.btn,.btn-group .btn+.btn-group,.btn-group .btn-group+.btn,.btn-group .btn-group+.btn-group{margin-left:-1px}.btn-toolbar{margin-left:-5px}.btn-toolbar .btn,.btn-toolbar .btn-group,.btn-toolbar .input-group{float:left}.btn-toolbar>.btn,.btn-toolbar>.btn-group,.btn-toolbar>.input-group{margin-left:5px}.btn-group>.btn:not(:first-child):not(:last-child):not(.dropdown-toggle){border-radius:0}.btn-group>.btn:first-child{margin-left:0}.btn-group>.btn:first-child:not(:last-child):not(.dropdown-toggle){border-top-right-radius:0;border-bottom-right-radius:0}.btn-group>.btn:last-child:not(:first-child),.btn-group>.dropdown-toggle:not(:first-child){border-top-left-radius:0;border-bottom-left-radius:0}.btn-group>.btn-group{float:left}.btn-group>.btn-group:not(:first-child):not(:last-child)>.btn{border-radius:0}.btn-group>.btn-group:first-child:not(:last-child)>.btn:last-child,.btn-group>.btn-group:first-child:not(:last-child)>.dropdown-toggle{border-top-right-radius:0;border-bottom-right-radius:0}.btn-group>.btn-group:last-child:not(:first-child)>.btn:first-child{border-top-left-radius:0;border-bottom-left-radius:0}.btn-group .dropdown-toggle:active,.btn-group.open .dropdown-toggle{outline:0}.btn-group>.btn+.dropdown-toggle{padding-right:8px;padding-left:8px}.btn-group>.btn-lg+.dropdown-toggle{padding-right:12px;padding-left:12px}.btn-group.open .dropdown-toggle{-webkit-box-shadow:inset 0 3px 5px rgba(0,0,0,.125);box-shadow:inset 0 3px 5px rgba(0,0,0,.125)}.btn-group.open .dropdown-toggle.btn-link{-webkit-box-shadow:none;box-shadow:none}.btn .caret{margin-left:0}.btn-lg .caret{border-width:5px 5px 0;border-bottom-width:0}.dropup .btn-lg .caret{border-width:0 5px 5px}.btn-group-vertical>.btn,.btn-group-vertical>.btn-group,.btn-group-vertical>.btn-group>.btn{display:block;float:none;width:100%;max-width:100%}.btn-group-vertical>.btn-group>.btn{float:none}.btn-group-vertical>.btn+.btn,.btn-group-vertical>.btn+.btn-group,.btn-group-vertical>.btn-group+.btn,.btn-group-vertical>.btn-group+.btn-group{margin-top:-1px;margin-left:0}.btn-group-vertical>.btn:not(:first-child):not(:last-child){border-radius:0}.btn-group-vertical>.btn:first-child:not(:last-child){border-top-right-radius:4px;border-bottom-right-radius:0;border-bottom-left-radius:0}.btn-group-vertical>.btn:last-child:not(:first-child){border-top-left-radius:0;border-top-right-radius:0;border-bottom-left-radius:4px}.btn-group-vertical>.btn-group:not(:first-child):not(:last-child)>.btn{border-radius:0}.btn-group-vertical>.btn-group:first-child:not(:last-child)>.btn:last-child,.btn-group-vertical>.btn-group:first-child:not(:last-child)>.dropdown-toggle{border-bottom-right-radius:0;border-bottom-left-radius:0}.btn-group-vertical>.btn-group:last-child:not(:first-child)>.btn:first-child{border-top-left-radius:0;border-top-right-radius:0}.btn-group-justified{display:table;width:100%;table-layout:fixed;border-collapse:separate}.btn-group-justified>.btn,.btn-group-justified>.btn-group{display:table-cell;float:none;width:1%}.btn-group-justified>.btn-group .btn{width:100%}.btn-group-justified>.btn-group .dropdown-menu{left:auto}[data-toggle=buttons]>.btn input[type=checkbox],[data-toggle=buttons]>.btn input[type=radio],[data-toggle=buttons]>.btn-group>.btn input[type=checkbox],[data-toggle=buttons]>.btn-group>.btn input[type=radio]{position:absolute;clip:rect(0,0,0,0);pointer-events:none}.input-group{position:relative;display:table;border-collapse:separate}.input-group[class*=col-]{float:none;padding-right:0;padding-left:0}.input-group .form-control{position:relative;z-index:2;float:left;width:100%;margin-bottom:0}.input-group-lg>.form-control,.input-group-lg>.input-group-addon,.input-group-lg>.input-group-btn>.btn{height:46px;padding:10px 16px;font-size:18px;line-height:1.3333333;border-radius:6px}select.input-group-lg>.form-control,select.input-group-lg>.input-group-addon,select.input-group-lg>.input-group-btn>.btn{height:46px;line-height:46px}select[multiple].input-group-lg>.form-control,select[multiple].input-group-lg>.input-group-addon,select[multiple].input-group-lg>.input-group-btn>.btn,textarea.input-group-lg>.form-control,textarea.input-group-lg>.input-group-addon,textarea.input-group-lg>.input-group-btn>.btn{height:auto}.input-group-sm>.form-control,.input-group-sm>.input-group-addon,.input-group-sm>.input-group-btn>.btn{height:30px;padding:5px 10px;font-size:12px;line-height:1.5;border-radius:3px}select.input-group-sm>.form-control,select.input-group-sm>.input-group-addon,select.input-group-sm>.input-group-btn>.btn{height:30px;line-height:30px}select[multiple].input-group-sm>.form-control,select[multiple].input-group-sm>.input-group-addon,select[multiple].input-group-sm>.input-group-btn>.btn,textarea.input-group-sm>.form-control,textarea.input-group-sm>.input-group-addon,textarea.input-group-sm>.input-group-btn>.btn{height:auto}.input-group .form-control,.input-group-addon,.input-group-btn{display:table-cell}.input-group .form-control:not(:first-child):not(:last-child),.input-group-addon:not(:first-child):not(:last-child),.input-group-btn:not(:first-child):not(:last-child){border-radius:0}.input-group-addon,.input-group-btn{width:1%;white-space:nowrap;vertical-align:middle}.input-group-addon{padding:6px 12px;font-size:14px;font-weight:400;line-height:1;color:#555;text-align:center;background-color:#eee;border:1px solid #ccc;border-radius:4px}.input-group-addon.input-sm{padding:5px 10px;font-size:12px;border-radius:3px}.input-group-addon.input-lg{padding:10px 16px;font-size:18px;border-radius:6px}.input-group-addon input[type=checkbox],.input-group-addon input[type=radio]{margin-top:0}.input-group .form-control:first-child,.input-group-addon:first-child,.input-group-btn:first-child>.btn,.input-group-btn:first-child>.btn-group>.btn,.input-group-btn:first-child>.dropdown-toggle,.input-group-btn:last-child>.btn-group:not(:last-child)>.btn,.input-group-btn:last-child>.btn:not(:last-child):not(.dropdown-toggle){border-top-right-radius:0;border-bottom-right-radius:0}.input-group-addon:first-child{border-right:0}.input-group .form-control:last-child,.input-group-addon:last-child,.input-group-btn:first-child>.btn-group:not(:first-child)>.btn,.input-group-btn:first-child>.btn:not(:first-child),.input-group-btn:last-child>.btn,.input-group-btn:last-child>.btn-group>.btn,.input-group-btn:last-child>.dropdown-toggle{border-top-left-radius:0;border-bottom-left-radius:0}.input-group-addon:last-child{border-left:0}.input-group-btn{position:relative;font-size:0;white-space:nowrap}.input-group-btn>.btn{position:relative}.input-group-btn>.btn+.btn{margin-left:-1px}.input-group-btn>.btn:active,.input-group-btn>.btn:focus,.input-group-btn>.btn:hover{z-index:2}.input-group-btn:first-child>.btn,.input-group-btn:first-child>.btn-group{margin-right:-1px}.input-group-btn:last-child>.btn,.input-group-btn:last-child>.btn-group{z-index:2;margin-left:-1px}.nav{padding-left:0;margin-bottom:0;list-style:none}.nav>li{position:relative;display:block}.nav>li>a{position:relative;display:block;padding:10px 15px}.nav>li>a:focus,.nav>li>a:hover{text-decoration:none;background-color:#eee}.nav>li.disabled>a{color:#777}.nav>li.disabled>a:focus,.nav>li.disabled>a:hover{color:#777;text-decoration:none;cursor:not-allowed;background-color:transparent}.nav .open>a,.nav .open>a:focus,.nav .open>a:hover{background-color:#eee;border-color:#337ab7}.nav .nav-divider{height:1px;margin:9px 0;overflow:hidden;background-color:#e5e5e5}.nav>li>a>img{max-width:none}.nav-tabs{border-bottom:1px solid #ddd}.nav-tabs>li{float:left;margin-bottom:-1px}.nav-tabs>li>a{margin-right:2px;line-height:1.42857143;border:1px solid transparent;border-radius:4px 4px 0 0}.nav-tabs>li>a:hover{border-color:#eee #eee #ddd}.nav-tabs>li.active>a,.nav-tabs>li.active>a:focus,.nav-tabs>li.active>a:hover{color:#555;cursor:default;background-color:#fff;border:1px solid #ddd;border-bottom-color:transparent}.nav-tabs.nav-justified{width:100%;border-bottom:0}.nav-tabs.nav-justified>li{float:none}.nav-tabs.nav-justified>li>a{margin-bottom:5px;text-align:center}.nav-tabs.nav-justified>.dropdown .dropdown-menu{top:auto;left:auto}@media (min-width:768px){.nav-tabs.nav-justified>li{display:table-cell;width:1%}.nav-tabs.nav-justified>li>a{margin-bottom:0}}.nav-tabs.nav-justified>li>a{margin-right:0;border-radius:4px}.nav-tabs.nav-justified>.active>a,.nav-tabs.nav-justified>.active>a:focus,.nav-tabs.nav-justified>.active>a:hover{border:1px solid #ddd}@media (min-width:768px){.nav-tabs.nav-justified>li>a{border-bottom:1px solid #ddd;border-radius:4px 4px 0 0}.nav-tabs.nav-justified>.active>a,.nav-tabs.nav-justified>.active>a:focus,.nav-tabs.nav-justified>.active>a:hover{border-bottom-color:#fff}}.nav-pills>li{float:left}.nav-pills>li>a{border-radius:4px}.nav-pills>li+li{margin-left:2px}.nav-pills>li.active>a,.nav-pills>li.active>a:focus,.nav-pills>li.active>a:hover{color:#fff;background-color:#337ab7}.nav-stacked>li{float:none}.nav-stacked>li+li{margin-top:2px;margin-left:0}.nav-justified{width:100%}.nav-justified>li{float:none}.nav-justified>li>a{margin-bottom:5px;text-align:center}.nav-justified>.dropdown .dropdown-menu{top:auto;left:auto}@media (min-width:768px){.nav-justified>li{display:table-cell;width:1%}.nav-justified>li>a{margin-bottom:0}}.nav-tabs-justified{border-bottom:0}.nav-tabs-justified>li>a{margin-right:0;border-radius:4px}.nav-tabs-justified>.active>a,.nav-tabs-justified>.active>a:focus,.nav-tabs-justified>.active>a:hover{border:1px solid #ddd}@media (min-width:768px){.nav-tabs-justified>li>a{border-bottom:1px solid #ddd;border-radius:4px 4px 0 0}.nav-tabs-justified>.active>a,.nav-tabs-justified>.active>a:focus,.nav-tabs-justified>.active>a:hover{border-bottom-color:#fff}}.tab-content>.tab-pane{display:none}.tab-content>.active{display:block}.nav-tabs .dropdown-menu{margin-top:-1px;border-top-left-radius:0;border-top-right-radius:0}.navbar{position:relative;min-height:50px;margin-bottom:20px;border:1px solid transparent}@media (min-width:768px){.navbar{border-radius:4px}}@media (min-width:768px){.navbar-header{float:left}}.navbar-collapse{padding-right:15px;padding-left:15px;overflow-x:visible;-webkit-overflow-scrolling:touch;border-top:1px solid transparent;-webkit-box-shadow:inset 0 1px 0 rgba(255,255,255,.1);box-shadow:inset 0 1px 0 rgba(255,255,255,.1)}.navbar-collapse.in{overflow-y:auto}@media (min-width:768px){.navbar-collapse{width:auto;border-top:0;-webkit-box-shadow:none;box-shadow:none}.navbar-collapse.collapse{display:block!important;height:auto!important;padding-bottom:0;overflow:visible!important}.navbar-collapse.in{overflow-y:visible}.navbar-fixed-bottom .navbar-collapse,.navbar-fixed-top .navbar-collapse,.navbar-static-top .navbar-collapse{padding-right:0;padding-left:0}}.navbar-fixed-bottom .navbar-collapse,.navbar-fixed-top .navbar-collapse{max-height:340px}@media (max-device-width:480px) and (orientation:landscape){.navbar-fixed-bottom .navbar-collapse,.navbar-fixed-top .navbar-collapse{max-height:200px}}.container-fluid>.navbar-collapse,.container-fluid>.navbar-header,.container>.navbar-collapse,.container>.navbar-header{margin-right:-15px;margin-left:-15px}@media (min-width:768px){.container-fluid>.navbar-collapse,.container-fluid>.navbar-header,.container>.navbar-collapse,.container>.navbar-header{margin-right:0;margin-left:0}}.navbar-static-top{z-index:1000;border-width:0 0 1px}@media (min-width:768px){.navbar-static-top{border-radius:0}}.navbar-fixed-bottom,.navbar-fixed-top{position:fixed;right:0;left:0;z-index:1030}@media (min-width:768px){.navbar-fixed-bottom,.navbar-fixed-top{border-radius:0}}.navbar-fixed-top{top:0;border-width:0 0 1px}.navbar-fixed-bottom{bottom:0;margin-bottom:0;border-width:1px 0 0}.navbar-brand{float:left;height:50px;padding:15px 15px;font-size:18px;line-height:20px}.navbar-brand:focus,.navbar-brand:hover{text-decoration:none}.navbar-brand>img{display:block}@media (min-width:768px){.navbar>.container .navbar-brand,.navbar>.container-fluid .navbar-brand{margin-left:-15px}}.navbar-toggle{position:relative;float:right;padding:9px 10px;margin-top:8px;margin-right:15px;margin-bottom:8px;background-color:transparent;background-image:none;border:1px solid transparent;border-radius:4px}.navbar-toggle:focus{outline:0}.navbar-toggle .icon-bar{display:block;width:22px;height:2px;border-radius:1px}.navbar-toggle .icon-bar+.icon-bar{margin-top:4px}@media (min-width:768px){.navbar-toggle{display:none}}.navbar-nav{margin:7.5px -15px}.navbar-nav>li>a{padding-top:10px;padding-bottom:10px;line-height:20px}@media (max-width:767px){.navbar-nav .open .dropdown-menu{position:static;float:none;width:auto;margin-top:0;background-color:transparent;border:0;-webkit-box-shadow:none;box-shadow:none}.navbar-nav .open .dropdown-menu .dropdown-header,.navbar-nav .open .dropdown-menu>li>a{padding:5px 15px 5px 25px}.navbar-nav .open .dropdown-menu>li>a{line-height:20px}.navbar-nav .open .dropdown-menu>li>a:focus,.navbar-nav .open .dropdown-menu>li>a:hover{background-image:none}}@media (min-width:768px){.navbar-nav{float:left;margin:0}.navbar-nav>li{float:left}.navbar-nav>li>a{padding-top:15px;padding-bottom:15px}}.navbar-form{padding:10px 15px;margin-top:8px;margin-right:-15px;margin-bottom:8px;margin-left:-15px;border-top:1px solid transparent;border-bottom:1px solid transparent;-webkit-box-shadow:inset 0 1px 0 rgba(255,255,255,.1),0 1px 0 rgba(255,255,255,.1);box-shadow:inset 0 1px 0 rgba(255,255,255,.1),0 1px 0 rgba(255,255,255,.1)}@media (min-width:768px){.navbar-form .form-group{display:inline-block;margin-bottom:0;vertical-align:middle}.navbar-form .form-control{display:inline-block;width:auto;vertical-align:middle}.navbar-form .form-control-static{display:inline-block}.navbar-form .input-group{display:inline-table;vertical-align:middle}.navbar-form .input-group .form-control,.navbar-form .input-group .input-group-addon,.navbar-form .input-group .input-group-btn{width:auto}.navbar-form .input-group>.form-control{width:100%}.navbar-form .control-label{margin-bottom:0;vertical-align:middle}.navbar-form .checkbox,.navbar-form .radio{display:inline-block;margin-top:0;margin-bottom:0;vertical-align:middle}.navbar-form .checkbox label,.navbar-form .radio label{padding-left:0}.navbar-form .checkbox input[type=checkbox],.navbar-form .radio input[type=radio]{position:relative;margin-left:0}.navbar-form .has-feedback .form-control-feedback{top:0}}@media (max-width:767px){.navbar-form .form-group{margin-bottom:5px}.navbar-form .form-group:last-child{margin-bottom:0}}@media (min-width:768px){.navbar-form{width:auto;padding-top:0;padding-bottom:0;margin-right:0;margin-left:0;border:0;-webkit-box-shadow:none;box-shadow:none}}.navbar-nav>li>.dropdown-menu{margin-top:0;border-top-left-radius:0;border-top-right-radius:0}.navbar-fixed-bottom .navbar-nav>li>.dropdown-menu{margin-bottom:0;border-top-left-radius:4px;border-top-right-radius:4px;border-bottom-right-radius:0;border-bottom-left-radius:0}.navbar-btn{margin-top:8px;margin-bottom:8px}.navbar-btn.btn-sm{margin-top:10px;margin-bottom:10px}.navbar-btn.btn-xs{margin-top:14px;margin-bottom:14px}.navbar-text{margin-top:15px;margin-bottom:15px}@media (min-width:768px){.navbar-text{float:left;margin-right:15px;margin-left:15px}}@media (min-width:768px){.navbar-left{float:left!important}.navbar-right{float:right!important;margin-right:-15px}.navbar-right~.navbar-right{margin-right:0}}.navbar-default{background-color:#f8f8f8;border-color:#e7e7e7}.navbar-default .navbar-brand{color:#777}.navbar-default .navbar-brand:focus,.navbar-default .navbar-brand:hover{color:#5e5e5e;background-color:transparent}.navbar-default .navbar-text{color:#777}.navbar-default .navbar-nav>li>a{color:#777}.navbar-default .navbar-nav>li>a:focus,.navbar-default .navbar-nav>li>a:hover{color:#333;background-color:transparent}.navbar-default .navbar-nav>.active>a,.navbar-default .navbar-nav>.active>a:focus,.navbar-default .navbar-nav>.active>a:hover{color:#555;background-color:#e7e7e7}.navbar-default .navbar-nav>.disabled>a,.navbar-default .navbar-nav>.disabled>a:focus,.navbar-default .navbar-nav>.disabled>a:hover{color:#ccc;background-color:transparent}.navbar-default .navbar-toggle{border-color:#ddd}.navbar-default .navbar-toggle:focus,.navbar-default .navbar-toggle:hover{background-color:#ddd}.navbar-default .navbar-toggle .icon-bar{background-color:#888}.navbar-default .navbar-collapse,.navbar-default .navbar-form{border-color:#e7e7e7}.navbar-default .navbar-nav>.open>a,.navbar-default .navbar-nav>.open>a:focus,.navbar-default .navbar-nav>.open>a:hover{color:#555;background-color:#e7e7e7}@media (max-width:767px){.navbar-default .navbar-nav .open .dropdown-menu>li>a{color:#777}.navbar-default .navbar-nav .open .dropdown-menu>li>a:focus,.navbar-default .navbar-nav .open .dropdown-menu>li>a:hover{color:#333;background-color:transparent}.navbar-default .navbar-nav .open .dropdown-menu>.active>a,.navbar-default .navbar-nav .open .dropdown-menu>.active>a:focus,.navbar-default .navbar-nav .open .dropdown-menu>.active>a:hover{color:#555;background-color:#e7e7e7}.navbar-default .navbar-nav .open .dropdown-menu>.disabled>a,.navbar-default .navbar-nav .open .dropdown-menu>.disabled>a:focus,.navbar-default .navbar-nav .open .dropdown-menu>.disabled>a:hover{color:#ccc;background-color:transparent}}.navbar-default .navbar-link{color:#777}.navbar-default .navbar-link:hover{color:#333}.navbar-default .btn-link{color:#777}.navbar-default .btn-link:focus,.navbar-default .btn-link:hover{color:#333}.navbar-default .btn-link[disabled]:focus,.navbar-default .btn-link[disabled]:hover,fieldset[disabled] .navbar-default .btn-link:focus,fieldset[disabled] .navbar-default .btn-link:hover{color:#ccc}.navbar-inverse{background-color:#222;border-color:#080808}.navbar-inverse .navbar-brand{color:#9d9d9d}.navbar-inverse .navbar-brand:focus,.navbar-inverse .navbar-brand:hover{color:#fff;background-color:transparent}.navbar-inverse .navbar-text{color:#9d9d9d}.navbar-inverse .navbar-nav>li>a{color:#9d9d9d}.navbar-inverse .navbar-nav>li>a:focus,.navbar-inverse .navbar-nav>li>a:hover{color:#fff;background-color:transparent}.navbar-inverse .navbar-nav>.active>a,.navbar-inverse .navbar-nav>.active>a:focus,.navbar-inverse .navbar-nav>.active>a:hover{color:#fff;background-color:#080808}.navbar-inverse .navbar-nav>.disabled>a,.navbar-inverse .navbar-nav>.disabled>a:focus,.navbar-inverse .navbar-nav>.disabled>a:hover{color:#444;background-color:transparent}.navbar-inverse .navbar-toggle{border-color:#333}.navbar-inverse .navbar-toggle:focus,.navbar-inverse .navbar-toggle:hover{background-color:#333}.navbar-inverse .navbar-toggle .icon-bar{background-color:#fff}.navbar-inverse .navbar-collapse,.navbar-inverse .navbar-form{border-color:#101010}.navbar-inverse .navbar-nav>.open>a,.navbar-inverse .navbar-nav>.open>a:focus,.navbar-inverse .navbar-nav>.open>a:hover{color:#fff;background-color:#080808}@media (max-width:767px){.navbar-inverse .navbar-nav .open .dropdown-menu>.dropdown-header{border-color:#080808}.navbar-inverse .navbar-nav .open .dropdown-menu .divider{background-color:#080808}.navbar-inverse .navbar-nav .open .dropdown-menu>li>a{color:#9d9d9d}.navbar-inverse .navbar-nav .open .dropdown-menu>li>a:focus,.navbar-inverse .navbar-nav .open .dropdown-menu>li>a:hover{color:#fff;background-color:transparent}.navbar-inverse .navbar-nav .open .dropdown-menu>.active>a,.navbar-inverse .navbar-nav .open .dropdown-menu>.active>a:focus,.navbar-inverse .navbar-nav .open .dropdown-menu>.active>a:hover{color:#fff;background-color:#080808}.navbar-inverse .navbar-nav .open .dropdown-menu>.disabled>a,.navbar-inverse .navbar-nav .open .dropdown-menu>.disabled>a:focus,.navbar-inverse .navbar-nav .open .dropdown-menu>.disabled>a:hover{color:#444;background-color:transparent}}.navbar-inverse .navbar-link{color:#9d9d9d}.navbar-inverse .navbar-link:hover{color:#fff}.navbar-inverse .btn-link{color:#9d9d9d}.navbar-inverse .btn-link:focus,.navbar-inverse .btn-link:hover{color:#fff}.navbar-inverse .btn-link[disabled]:focus,.navbar-inverse .btn-link[disabled]:hover,fieldset[disabled] .navbar-inverse .btn-link:focus,fieldset[disabled] .navbar-inverse .btn-link:hover{color:#444}.breadcrumb{padding:8px 15px;margin-bottom:20px;list-style:none;background-color:#f5f5f5;border-radius:4px}.breadcrumb>li{display:inline-block}.breadcrumb>li+li:before{padding:0 5px;color:#ccc;content:"/\00a0"}.breadcrumb>.active{color:#777}.pagination{display:inline-block;padding-left:0;margin:20px 0;border-radius:4px}.pagination>li{display:inline}.pagination>li>a,.pagination>li>span{position:relative;float:left;padding:6px 12px;margin-left:-1px;line-height:1.42857143;color:#337ab7;text-decoration:none;background-color:#fff;border:1px solid #ddd}.pagination>li:first-child>a,.pagination>li:first-child>span{margin-left:0;border-top-left-radius:4px;border-bottom-left-radius:4px}.pagination>li:last-child>a,.pagination>li:last-child>span{border-top-right-radius:4px;border-bottom-right-radius:4px}.pagination>li>a:focus,.pagination>li>a:hover,.pagination>li>span:focus,.pagination>li>span:hover{z-index:3;color:#23527c;background-color:#eee;border-color:#ddd}.pagination>.active>a,.pagination>.active>a:focus,.pagination>.active>a:hover,.pagination>.active>span,.pagination>.active>span:focus,.pagination>.active>span:hover{z-index:2;color:#fff;cursor:default;background-color:#337ab7;border-color:#337ab7}.pagination>.disabled>a,.pagination>.disabled>a:focus,.pagination>.disabled>a:hover,.pagination>.disabled>span,.pagination>.disabled>span:focus,.pagination>.disabled>span:hover{color:#777;cursor:not-allowed;background-color:#fff;border-color:#ddd}.pagination-lg>li>a,.pagination-lg>li>span{padding:10px 16px;font-size:18px;line-height:1.3333333}.pagination-lg>li:first-child>a,.pagination-lg>li:first-child>span{border-top-left-radius:6px;border-bottom-left-radius:6px}.pagination-lg>li:last-child>a,.pagination-lg>li:last-child>span{border-top-right-radius:6px;border-bottom-right-radius:6px}.pagination-sm>li>a,.pagination-sm>li>span{padding:5px 10px;font-size:12px;line-height:1.5}.pagination-sm>li:first-child>a,.pagination-sm>li:first-child>span{border-top-left-radius:3px;border-bottom-left-radius:3px}.pagination-sm>li:last-child>a,.pagination-sm>li:last-child>span{border-top-right-radius:3px;border-bottom-right-radius:3px}.pager{padding-left:0;margin:20px 0;text-align:center;list-style:none}.pager li{display:inline}.pager li>a,.pager li>span{display:inline-block;padding:5px 14px;background-color:#fff;border:1px solid #ddd;border-radius:15px}.pager li>a:focus,.pager li>a:hover{text-decoration:none;background-color:#eee}.pager .next>a,.pager .next>span{float:right}.pager .previous>a,.pager .previous>span{float:left}.pager .disabled>a,.pager .disabled>a:focus,.pager .disabled>a:hover,.pager .disabled>span{color:#777;cursor:not-allowed;background-color:#fff}.label{display:inline;padding:.2em .6em .3em;font-size:75%;font-weight:700;line-height:1;color:#fff;text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:.25em}a.label:focus,a.label:hover{color:#fff;text-decoration:none;cursor:pointer}.label:empty{display:none}.btn .label{position:relative;top:-1px}.label-default{background-color:#777}.label-default[href]:focus,.label-default[href]:hover{background-color:#5e5e5e}.label-primary{background-color:#337ab7}.label-primary[href]:focus,.label-primary[href]:hover{background-color:#286090}.label-success{background-color:#5cb85c}.label-success[href]:focus,.label-success[href]:hover{background-color:#449d44}.label-info{background-color:#5bc0de}.label-info[href]:focus,.label-info[href]:hover{background-color:#31b0d5}.label-warning{background-color:#f0ad4e}.label-warning[href]:focus,.label-warning[href]:hover{background-color:#ec971f}.label-danger{background-color:#d9534f}.label-danger[href]:focus,.label-danger[href]:hover{background-color:#c9302c}.badge{display:inline-block;min-width:10px;padding:3px 7px;font-size:12px;font-weight:700;line-height:1;color:#fff;text-align:center;white-space:nowrap;vertical-align:middle;background-color:#777;border-radius:10px}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.btn-group-xs>.btn .badge,.btn-xs .badge{top:0;padding:1px 5px}a.badge:focus,a.badge:hover{color:#fff;text-decoration:none;cursor:pointer}.list-group-item.active>.badge,.nav-pills>.active>a>.badge{color:#337ab7;background-color:#fff}.list-group-item>.badge{float:right}.list-group-item>.badge+.badge{margin-right:5px}.nav-pills>li>a>.badge{margin-left:3px}.jumbotron{padding-top:30px;padding-bottom:30px;margin-bottom:30px;color:inherit;background-color:#eee}.jumbotron .h1,.jumbotron h1{color:inherit}.jumbotron p{margin-bottom:15px;font-size:21px;font-weight:200}.jumbotron>hr{border-top-color:#d5d5d5}.container .jumbotron,.container-fluid .jumbotron{border-radius:6px}.jumbotron .container{max-width:100%}@media screen and (min-width:768px){.jumbotron{padding-top:48px;padding-bottom:48px}.container .jumbotron,.container-fluid .jumbotron{padding-right:60px;padding-left:60px}.jumbotron .h1,.jumbotron h1{font-size:63px}}.thumbnail{display:block;padding:4px;margin-bottom:20px;line-height:1.42857143;background-color:#fff;border:1px solid #ddd;border-radius:4px;-webkit-transition:border .2s ease-in-out;-o-transition:border .2s ease-in-out;transition:border .2s ease-in-out}.thumbnail a>img,.thumbnail>img{margin-right:auto;margin-left:auto}a.thumbnail.active,a.thumbnail:focus,a.thumbnail:hover{border-color:#337ab7}.thumbnail .caption{padding:9px;color:#333}.alert{padding:15px;margin-bottom:20px;border:1px solid transparent;border-radius:4px}.alert h4{margin-top:0;color:inherit}.alert .alert-link{font-weight:700}.alert>p,.alert>ul{margin-bottom:0}.alert>p+p{margin-top:5px}.alert-dismissable,.alert-dismissible{padding-right:35px}.alert-dismissable .close,.alert-dismissible .close{position:relative;top:-2px;right:-21px;color:inherit}.alert-success{color:#3c763d;background-color:#dff0d8;border-color:#d6e9c6}.alert-success hr{border-top-color:#c9e2b3}.alert-success .alert-link{color:#2b542c}.alert-info{color:#31708f;background-color:#d9edf7;border-color:#bce8f1}.alert-info hr{border-top-color:#a6e1ec}.alert-info .alert-link{color:#245269}.alert-warning{color:#8a6d3b;background-color:#fcf8e3;border-color:#faebcc}.alert-warning hr{border-top-color:#f7e1b5}.alert-warning .alert-link{color:#66512c}.alert-danger{color:#a94442;background-color:#f2dede;border-color:#ebccd1}.alert-danger hr{border-top-color:#e4b9c0}.alert-danger .alert-link{color:#843534}@-webkit-keyframes progress-bar-stripes{from{background-position:40px 0}to{background-position:0 0}}@-o-keyframes progress-bar-stripes{from{background-position:40px 0}to{background-position:0 0}}@keyframes progress-bar-stripes{from{background-position:40px 0}to{background-position:0 0}}.progress{height:20px;margin-bottom:20px;overflow:hidden;background-color:#f5f5f5;border-radius:4px;-webkit-box-shadow:inset 0 1px 2px rgba(0,0,0,.1);box-shadow:inset 0 1px 2px rgba(0,0,0,.1)}.progress-bar{float:left;width:0;height:100%;font-size:12px;line-height:20px;color:#fff;text-align:center;background-color:#337ab7;-webkit-box-shadow:inset 0 -1px 0 rgba(0,0,0,.15);box-shadow:inset 0 -1px 0 rgba(0,0,0,.15);-webkit-transition:width .6s ease;-o-transition:width .6s ease;transition:width .6s ease}.progress-bar-striped,.progress-striped .progress-bar{background-image:-webkit-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:-o-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);-webkit-background-size:40px 40px;background-size:40px 40px}.progress-bar.active,.progress.active .progress-bar{-webkit-animation:progress-bar-stripes 2s linear infinite;-o-animation:progress-bar-stripes 2s linear infinite;animation:progress-bar-stripes 2s linear infinite}.progress-bar-success{background-color:#5cb85c}.progress-striped .progress-bar-success{background-image:-webkit-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:-o-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent)}.progress-bar-info{background-color:#5bc0de}.progress-striped .progress-bar-info{background-image:-webkit-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:-o-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent)}.progress-bar-warning{background-color:#f0ad4e}.progress-striped .progress-bar-warning{background-image:-webkit-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:-o-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent)}.progress-bar-danger{background-color:#d9534f}.progress-striped .progress-bar-danger{background-image:-webkit-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:-o-linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent);background-image:linear-gradient(45deg,rgba(255,255,255,.15) 25%,transparent 25%,transparent 50%,rgba(255,255,255,.15) 50%,rgba(255,255,255,.15) 75%,transparent 75%,transparent)}.media{margin-top:15px}.media:first-child{margin-top:0}.media,.media-body{overflow:hidden;zoom:1}.media-body{width:10000px}.media-object{display:block}.media-object.img-thumbnail{max-width:none}.media-right,.media>.pull-right{padding-left:10px}.media-left,.media>.pull-left{padding-right:10px}.media-body,.media-left,.media-right{display:table-cell;vertical-align:top}.media-middle{vertical-align:middle}.media-bottom{vertical-align:bottom}.media-heading{margin-top:0;margin-bottom:5px}.media-list{padding-left:0;list-style:none}.list-group{padding-left:0;margin-bottom:20px}.list-group-item{position:relative;display:block;padding:10px 15px;margin-bottom:-1px;background-color:#fff;border:1px solid #ddd}.list-group-item:first-child{border-top-left-radius:4px;border-top-right-radius:4px}.list-group-item:last-child{margin-bottom:0;border-bottom-right-radius:4px;border-bottom-left-radius:4px}a.list-group-item,button.list-group-item{color:#555}a.list-group-item .list-group-item-heading,button.list-group-item .list-group-item-heading{color:#333}a.list-group-item:focus,a.list-group-item:hover,button.list-group-item:focus,button.list-group-item:hover{color:#555;text-decoration:none;background-color:#f5f5f5}button.list-group-item{width:100%;text-align:left}.list-group-item.disabled,.list-group-item.disabled:focus,.list-group-item.disabled:hover{color:#777;cursor:not-allowed;background-color:#eee}.list-group-item.disabled .list-group-item-heading,.list-group-item.disabled:focus .list-group-item-heading,.list-group-item.disabled:hover .list-group-item-heading{color:inherit}.list-group-item.disabled .list-group-item-text,.list-group-item.disabled:focus .list-group-item-text,.list-group-item.disabled:hover .list-group-item-text{color:#777}.list-group-item.active,.list-group-item.active:focus,.list-group-item.active:hover{z-index:2;color:#fff;background-color:#337ab7;border-color:#337ab7}.list-group-item.active .list-group-item-heading,.list-group-item.active .list-group-item-heading>.small,.list-group-item.active .list-group-item-heading>small,.list-group-item.active:focus .list-group-item-heading,.list-group-item.active:focus .list-group-item-heading>.small,.list-group-item.active:focus .list-group-item-heading>small,.list-group-item.active:hover .list-group-item-heading,.list-group-item.active:hover .list-group-item-heading>.small,.list-group-item.active:hover .list-group-item-heading>small{color:inherit}.list-group-item.active .list-group-item-text,.list-group-item.active:focus .list-group-item-text,.list-group-item.active:hover .list-group-item-text{color:#c7ddef}.list-group-item-success{color:#3c763d;background-color:#dff0d8}a.list-group-item-success,button.list-group-item-success{color:#3c763d}a.list-group-item-success .list-group-item-heading,button.list-group-item-success .list-group-item-heading{color:inherit}a.list-group-item-success:focus,a.list-group-item-success:hover,button.list-group-item-success:focus,button.list-group-item-success:hover{color:#3c763d;background-color:#d0e9c6}a.list-group-item-success.active,a.list-group-item-success.active:focus,a.list-group-item-success.active:hover,button.list-group-item-success.active,button.list-group-item-success.active:focus,button.list-group-item-success.active:hover{color:#fff;background-color:#3c763d;border-color:#3c763d}.list-group-item-info{color:#31708f;background-color:#d9edf7}a.list-group-item-info,button.list-group-item-info{color:#31708f}a.list-group-item-info .list-group-item-heading,button.list-group-item-info .list-group-item-heading{color:inherit}a.list-group-item-info:focus,a.list-group-item-info:hover,button.list-group-item-info:focus,button.list-group-item-info:hover{color:#31708f;background-color:#c4e3f3}a.list-group-item-info.active,a.list-group-item-info.active:focus,a.list-group-item-info.active:hover,button.list-group-item-info.active,button.list-group-item-info.active:focus,button.list-group-item-info.active:hover{color:#fff;background-color:#31708f;border-color:#31708f}.list-group-item-warning{color:#8a6d3b;background-color:#fcf8e3}a.list-group-item-warning,button.list-group-item-warning{color:#8a6d3b}a.list-group-item-warning .list-group-item-heading,button.list-group-item-warning .list-group-item-heading{color:inherit}a.list-group-item-warning:focus,a.list-group-item-warning:hover,button.list-group-item-warning:focus,button.list-group-item-warning:hover{color:#8a6d3b;background-color:#faf2cc}a.list-group-item-warning.active,a.list-group-item-warning.active:focus,a.list-group-item-warning.active:hover,button.list-group-item-warning.active,button.list-group-item-warning.active:focus,button.list-group-item-warning.active:hover{color:#fff;background-color:#8a6d3b;border-color:#8a6d3b}.list-group-item-danger{color:#a94442;background-color:#f2dede}a.list-group-item-danger,button.list-group-item-danger{color:#a94442}a.list-group-item-danger .list-group-item-heading,button.list-group-item-danger .list-group-item-heading{color:inherit}a.list-group-item-danger:focus,a.list-group-item-danger:hover,button.list-group-item-danger:focus,button.list-group-item-danger:hover{color:#a94442;background-color:#ebcccc}a.list-group-item-danger.active,a.list-group-item-danger.active:focus,a.list-group-item-danger.active:hover,button.list-group-item-danger.active,button.list-group-item-danger.active:focus,button.list-group-item-danger.active:hover{color:#fff;background-color:#a94442;border-color:#a94442}.list-group-item-heading{margin-top:0;margin-bottom:5px}.list-group-item-text{margin-bottom:0;line-height:1.3}.panel{margin-bottom:20px;background-color:#fff;border:1px solid transparent;border-radius:4px;-webkit-box-shadow:0 1px 1px rgba(0,0,0,.05);box-shadow:0 1px 1px rgba(0,0,0,.05)}.panel-body{padding:15px}.panel-heading{padding:10px 15px;border-bottom:1px solid transparent;border-top-left-radius:3px;border-top-right-radius:3px}.panel-heading>.dropdown .dropdown-toggle{color:inherit}.panel-title{margin-top:0;margin-bottom:0;font-size:16px;color:inherit}.panel-title>.small,.panel-title>.small>a,.panel-title>a,.panel-title>small,.panel-title>small>a{color:inherit}.panel-footer{padding:10px 15px;background-color:#f5f5f5;border-top:1px solid #ddd;border-bottom-right-radius:3px;border-bottom-left-radius:3px}.panel>.list-group,.panel>.panel-collapse>.list-group{margin-bottom:0}.panel>.list-group .list-group-item,.panel>.panel-collapse>.list-group .list-group-item{border-width:1px 0;border-radius:0}.panel>.list-group:first-child .list-group-item:first-child,.panel>.panel-collapse>.list-group:first-child .list-group-item:first-child{border-top:0;border-top-left-radius:3px;border-top-right-radius:3px}.panel>.list-group:last-child .list-group-item:last-child,.panel>.panel-collapse>.list-group:last-child .list-group-item:last-child{border-bottom:0;border-bottom-right-radius:3px;border-bottom-left-radius:3px}.panel>.panel-heading+.panel-collapse>.list-group .list-group-item:first-child{border-top-left-radius:0;border-top-right-radius:0}.panel-heading+.list-group .list-group-item:first-child{border-top-width:0}.list-group+.panel-footer{border-top-width:0}.panel>.panel-collapse>.table,.panel>.table,.panel>.table-responsive>.table{margin-bottom:0}.panel>.panel-collapse>.table caption,.panel>.table caption,.panel>.table-responsive>.table caption{padding-right:15px;padding-left:15px}.panel>.table-responsive:first-child>.table:first-child,.panel>.table:first-child{border-top-left-radius:3px;border-top-right-radius:3px}.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child,.panel>.table:first-child>tbody:first-child>tr:first-child,.panel>.table:first-child>thead:first-child>tr:first-child{border-top-left-radius:3px;border-top-right-radius:3px}.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child td:first-child,.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child th:first-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child td:first-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child th:first-child,.panel>.table:first-child>tbody:first-child>tr:first-child td:first-child,.panel>.table:first-child>tbody:first-child>tr:first-child th:first-child,.panel>.table:first-child>thead:first-child>tr:first-child td:first-child,.panel>.table:first-child>thead:first-child>tr:first-child th:first-child{border-top-left-radius:3px}.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child td:last-child,.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child th:last-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child td:last-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child th:last-child,.panel>.table:first-child>tbody:first-child>tr:first-child td:last-child,.panel>.table:first-child>tbody:first-child>tr:first-child th:last-child,.panel>.table:first-child>thead:first-child>tr:first-child td:last-child,.panel>.table:first-child>thead:first-child>tr:first-child th:last-child{border-top-right-radius:3px}.panel>.table-responsive:last-child>.table:last-child,.panel>.table:last-child{border-bottom-right-radius:3px;border-bottom-left-radius:3px}.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child,.panel>.table:last-child>tbody:last-child>tr:last-child,.panel>.table:last-child>tfoot:last-child>tr:last-child{border-bottom-right-radius:3px;border-bottom-left-radius:3px}.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child td:first-child,.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child th:first-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child td:first-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child th:first-child,.panel>.table:last-child>tbody:last-child>tr:last-child td:first-child,.panel>.table:last-child>tbody:last-child>tr:last-child th:first-child,.panel>.table:last-child>tfoot:last-child>tr:last-child td:first-child,.panel>.table:last-child>tfoot:last-child>tr:last-child th:first-child{border-bottom-left-radius:3px}.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child td:last-child,.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child th:last-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child td:last-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child th:last-child,.panel>.table:last-child>tbody:last-child>tr:last-child td:last-child,.panel>.table:last-child>tbody:last-child>tr:last-child th:last-child,.panel>.table:last-child>tfoot:last-child>tr:last-child td:last-child,.panel>.table:last-child>tfoot:last-child>tr:last-child th:last-child{border-bottom-right-radius:3px}.panel>.panel-body+.table,.panel>.panel-body+.table-responsive,.panel>.table+.panel-body,.panel>.table-responsive+.panel-body{border-top:1px solid #ddd}.panel>.table>tbody:first-child>tr:first-child td,.panel>.table>tbody:first-child>tr:first-child th{border-top:0}.panel>.table-bordered,.panel>.table-responsive>.table-bordered{border:0}.panel>.table-bordered>tbody>tr>td:first-child,.panel>.table-bordered>tbody>tr>th:first-child,.panel>.table-bordered>tfoot>tr>td:first-child,.panel>.table-bordered>tfoot>tr>th:first-child,.panel>.table-bordered>thead>tr>td:first-child,.panel>.table-bordered>thead>tr>th:first-child,.panel>.table-responsive>.table-bordered>tbody>tr>td:first-child,.panel>.table-responsive>.table-bordered>tbody>tr>th:first-child,.panel>.table-responsive>.table-bordered>tfoot>tr>td:first-child,.panel>.table-responsive>.table-bordered>tfoot>tr>th:first-child,.panel>.table-responsive>.table-bordered>thead>tr>td:first-child,.panel>.table-responsive>.table-bordered>thead>tr>th:first-child{border-left:0}.panel>.table-bordered>tbody>tr>td:last-child,.panel>.table-bordered>tbody>tr>th:last-child,.panel>.table-bordered>tfoot>tr>td:last-child,.panel>.table-bordered>tfoot>tr>th:last-child,.panel>.table-bordered>thead>tr>td:last-child,.panel>.table-bordered>thead>tr>th:last-child,.panel>.table-responsive>.table-bordered>tbody>tr>td:last-child,.panel>.table-responsive>.table-bordered>tbody>tr>th:last-child,.panel>.table-responsive>.table-bordered>tfoot>tr>td:last-child,.panel>.table-responsive>.table-bordered>tfoot>tr>th:last-child,.panel>.table-responsive>.table-bordered>thead>tr>td:last-child,.panel>.table-responsive>.table-bordered>thead>tr>th:last-child{border-right:0}.panel>.table-bordered>tbody>tr:first-child>td,.panel>.table-bordered>tbody>tr:first-child>th,.panel>.table-bordered>thead>tr:first-child>td,.panel>.table-bordered>thead>tr:first-child>th,.panel>.table-responsive>.table-bordered>tbody>tr:first-child>td,.panel>.table-responsive>.table-bordered>tbody>tr:first-child>th,.panel>.table-responsive>.table-bordered>thead>tr:first-child>td,.panel>.table-responsive>.table-bordered>thead>tr:first-child>th{border-bottom:0}.panel>.table-bordered>tbody>tr:last-child>td,.panel>.table-bordered>tbody>tr:last-child>th,.panel>.table-bordered>tfoot>tr:last-child>td,.panel>.table-bordered>tfoot>tr:last-child>th,.panel>.table-responsive>.table-bordered>tbody>tr:last-child>td,.panel>.table-responsive>.table-bordered>tbody>tr:last-child>th,.panel>.table-responsive>.table-bordered>tfoot>tr:last-child>td,.panel>.table-responsive>.table-bordered>tfoot>tr:last-child>th{border-bottom:0}.panel>.table-responsive{margin-bottom:0;border:0}.panel-group{margin-bottom:20px}.panel-group .panel{margin-bottom:0;border-radius:4px}.panel-group .panel+.panel{margin-top:5px}.panel-group .panel-heading{border-bottom:0}.panel-group .panel-heading+.panel-collapse>.list-group,.panel-group .panel-heading+.panel-collapse>.panel-body{border-top:1px solid #ddd}.panel-group .panel-footer{border-top:0}.panel-group .panel-footer+.panel-collapse .panel-body{border-bottom:1px solid #ddd}.panel-default{border-color:#ddd}.panel-default>.panel-heading{color:#333;background-color:#f5f5f5;border-color:#ddd}.panel-default>.panel-heading+.panel-collapse>.panel-body{border-top-color:#ddd}.panel-default>.panel-heading .badge{color:#f5f5f5;background-color:#333}.panel-default>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#ddd}.panel-primary{border-color:#337ab7}.panel-primary>.panel-heading{color:#fff;background-color:#337ab7;border-color:#337ab7}.panel-primary>.panel-heading+.panel-collapse>.panel-body{border-top-color:#337ab7}.panel-primary>.panel-heading .badge{color:#337ab7;background-color:#fff}.panel-primary>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#337ab7}.panel-success{border-color:#d6e9c6}.panel-success>.panel-heading{color:#3c763d;background-color:#dff0d8;border-color:#d6e9c6}.panel-success>.panel-heading+.panel-collapse>.panel-body{border-top-color:#d6e9c6}.panel-success>.panel-heading .badge{color:#dff0d8;background-color:#3c763d}.panel-success>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#d6e9c6}.panel-info{border-color:#bce8f1}.panel-info>.panel-heading{color:#31708f;background-color:#d9edf7;border-color:#bce8f1}.panel-info>.panel-heading+.panel-collapse>.panel-body{border-top-color:#bce8f1}.panel-info>.panel-heading .badge{color:#d9edf7;background-color:#31708f}.panel-info>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#bce8f1}.panel-warning{border-color:#faebcc}.panel-warning>.panel-heading{color:#8a6d3b;background-color:#fcf8e3;border-color:#faebcc}.panel-warning>.panel-heading+.panel-collapse>.panel-body{border-top-color:#faebcc}.panel-warning>.panel-heading .badge{color:#fcf8e3;background-color:#8a6d3b}.panel-warning>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#faebcc}.panel-danger{border-color:#ebccd1}.panel-danger>.panel-heading{color:#a94442;background-color:#f2dede;border-color:#ebccd1}.panel-danger>.panel-heading+.panel-collapse>.panel-body{border-top-color:#ebccd1}.panel-danger>.panel-heading .badge{color:#f2dede;background-color:#a94442}.panel-danger>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#ebccd1}.embed-responsive{position:relative;display:block;height:0;padding:0;overflow:hidden}.embed-responsive .embed-responsive-item,.embed-responsive embed,.embed-responsive iframe,.embed-responsive object,.embed-responsive video{position:absolute;top:0;bottom:0;left:0;width:100%;height:100%;border:0}.embed-responsive-16by9{padding-bottom:56.25%}.embed-responsive-4by3{padding-bottom:75%}.well{min-height:20px;padding:19px;margin-bottom:20px;background-color:#f5f5f5;border:1px solid #e3e3e3;border-radius:4px;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,.05);box-shadow:inset 0 1px 1px rgba(0,0,0,.05)}.well blockquote{border-color:#ddd;border-color:rgba(0,0,0,.15)}.well-lg{padding:24px;border-radius:6px}.well-sm{padding:9px;border-radius:3px}.close{float:right;font-size:21px;font-weight:700;line-height:1;color:#000;text-shadow:0 1px 0 #fff;filter:alpha(opacity=20);opacity:.2}.close:focus,.close:hover{color:#000;text-decoration:none;cursor:pointer;filter:alpha(opacity=50);opacity:.5}button.close{-webkit-appearance:none;padding:0;cursor:pointer;background:0 0;border:0}.modal-open{overflow:hidden}.modal{position:fixed;top:0;right:0;bottom:0;left:0;z-index:1050;display:none;overflow:hidden;-webkit-overflow-scrolling:touch;outline:0}.modal.fade .modal-dialog{-webkit-transition:-webkit-transform .3s ease-out;-o-transition:-o-transform .3s ease-out;transition:transform .3s ease-out;-webkit-transform:translate(0,-25%);-ms-transform:translate(0,-25%);-o-transform:translate(0,-25%);transform:translate(0,-25%)}.modal.in .modal-dialog{-webkit-transform:translate(0,0);-ms-transform:translate(0,0);-o-transform:translate(0,0);transform:translate(0,0)}.modal-open .modal{overflow-x:hidden;overflow-y:auto}.modal-dialog{position:relative;width:auto;margin:10px}.modal-content{position:relative;background-color:#fff;-webkit-background-clip:padding-box;background-clip:padding-box;border:1px solid #999;border:1px solid rgba(0,0,0,.2);border-radius:6px;outline:0;-webkit-box-shadow:0 3px 9px rgba(0,0,0,.5);box-shadow:0 3px 9px rgba(0,0,0,.5)}.modal-backdrop{position:fixed;top:0;right:0;bottom:0;left:0;z-index:1040;background-color:#000}.modal-backdrop.fade{filter:alpha(opacity=0);opacity:0}.modal-backdrop.in{filter:alpha(opacity=50);opacity:.5}.modal-header{min-height:16.43px;padding:15px;border-bottom:1px solid #e5e5e5}.modal-header .close{margin-top:-2px}.modal-title{margin:0;line-height:1.42857143}.modal-body{position:relative;padding:15px}.modal-footer{padding:15px;text-align:right;border-top:1px solid #e5e5e5}.modal-footer .btn+.btn{margin-bottom:0;margin-left:5px}.modal-footer .btn-group .btn+.btn{margin-left:-1px}.modal-footer .btn-block+.btn-block{margin-left:0}.modal-scrollbar-measure{position:absolute;top:-9999px;width:50px;height:50px;overflow:scroll}@media (min-width:768px){.modal-dialog{width:600px;margin:30px auto}.modal-content{-webkit-box-shadow:0 5px 15px rgba(0,0,0,.5);box-shadow:0 5px 15px rgba(0,0,0,.5)}.modal-sm{width:300px}}@media (min-width:992px){.modal-lg{width:900px}}.tooltip{position:absolute;z-index:1070;display:block;font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-size:12px;font-style:normal;font-weight:400;line-height:1.42857143;text-align:left;text-align:start;text-decoration:none;text-shadow:none;text-transform:none;letter-spacing:normal;word-break:normal;word-spacing:normal;word-wrap:normal;white-space:normal;filter:alpha(opacity=0);opacity:0;line-break:auto}.tooltip.in{filter:alpha(opacity=90);opacity:.9}.tooltip.top{padding:5px 0;margin-top:-3px}.tooltip.right{padding:0 5px;margin-left:3px}.tooltip.bottom{padding:5px 0;margin-top:3px}.tooltip.left{padding:0 5px;margin-left:-3px}.tooltip-inner{max-width:200px;padding:3px 8px;color:#fff;text-align:center;background-color:#000;border-radius:4px}.tooltip-arrow{position:absolute;width:0;height:0;border-color:transparent;border-style:solid}.tooltip.top .tooltip-arrow{bottom:0;left:50%;margin-left:-5px;border-width:5px 5px 0;border-top-color:#000}.tooltip.top-left .tooltip-arrow{right:5px;bottom:0;margin-bottom:-5px;border-width:5px 5px 0;border-top-color:#000}.tooltip.top-right .tooltip-arrow{bottom:0;left:5px;margin-bottom:-5px;border-width:5px 5px 0;border-top-color:#000}.tooltip.right .tooltip-arrow{top:50%;left:0;margin-top:-5px;border-width:5px 5px 5px 0;border-right-color:#000}.tooltip.left .tooltip-arrow{top:50%;right:0;margin-top:-5px;border-width:5px 0 5px 5px;border-left-color:#000}.tooltip.bottom .tooltip-arrow{top:0;left:50%;margin-left:-5px;border-width:0 5px 5px;border-bottom-color:#000}.tooltip.bottom-left .tooltip-arrow{top:0;right:5px;margin-top:-5px;border-width:0 5px 5px;border-bottom-color:#000}.tooltip.bottom-right .tooltip-arrow{top:0;left:5px;margin-top:-5px;border-width:0 5px 5px;border-bottom-color:#000}.popover{position:absolute;top:0;left:0;z-index:1060;display:none;max-width:276px;padding:1px;font-family:"Helvetica Neue",Helvetica,Arial,sans-serif;font-size:14px;font-style:normal;font-weight:400;line-height:1.42857143;text-align:left;text-align:start;text-decoration:none;text-shadow:none;text-transform:none;letter-spacing:normal;word-break:normal;word-spacing:normal;word-wrap:normal;white-space:normal;background-color:#fff;-webkit-background-clip:padding-box;background-clip:padding-box;border:1px solid #ccc;border:1px solid rgba(0,0,0,.2);border-radius:6px;-webkit-box-shadow:0 5px 10px rgba(0,0,0,.2);box-shadow:0 5px 10px rgba(0,0,0,.2);line-break:auto}.popover.top{margin-top:-10px}.popover.right{margin-left:10px}.popover.bottom{margin-top:10px}.popover.left{margin-left:-10px}.popover-title{padding:8px 14px;margin:0;font-size:14px;background-color:#f7f7f7;border-bottom:1px solid #ebebeb;border-radius:5px 5px 0 0}.popover-content{padding:9px 14px}.popover>.arrow,.popover>.arrow:after{position:absolute;display:block;width:0;height:0;border-color:transparent;border-style:solid}.popover>.arrow{border-width:11px}.popover>.arrow:after{content:"";border-width:10px}.popover.top>.arrow{bottom:-11px;left:50%;margin-left:-11px;border-top-color:#999;border-top-color:rgba(0,0,0,.25);border-bottom-width:0}.popover.top>.arrow:after{bottom:1px;margin-left:-10px;content:" ";border-top-color:#fff;border-bottom-width:0}.popover.right>.arrow{top:50%;left:-11px;margin-top:-11px;border-right-color:#999;border-right-color:rgba(0,0,0,.25);border-left-width:0}.popover.right>.arrow:after{bottom:-10px;left:1px;content:" ";border-right-color:#fff;border-left-width:0}.popover.bottom>.arrow{top:-11px;left:50%;margin-left:-11px;border-top-width:0;border-bottom-color:#999;border-bottom-color:rgba(0,0,0,.25)}.popover.bottom>.arrow:after{top:1px;margin-left:-10px;content:" ";border-top-width:0;border-bottom-color:#fff}.popover.left>.arrow{top:50%;right:-11px;margin-top:-11px;border-right-width:0;border-left-color:#999;border-left-color:rgba(0,0,0,.25)}.popover.left>.arrow:after{right:1px;bottom:-10px;content:" ";border-right-width:0;border-left-color:#fff}.carousel{position:relative}.carousel-inner{position:relative;width:100%;overflow:hidden}.carousel-inner>.item{position:relative;display:none;-webkit-transition:.6s ease-in-out left;-o-transition:.6s ease-in-out left;transition:.6s ease-in-out left}.carousel-inner>.item>a>img,.carousel-inner>.item>img{line-height:1}@media all and (transform-3d),(-webkit-transform-3d){.carousel-inner>.item{-webkit-transition:-webkit-transform .6s ease-in-out;-o-transition:-o-transform .6s ease-in-out;transition:transform .6s ease-in-out;-webkit-backface-visibility:hidden;backface-visibility:hidden;-webkit-perspective:1000px;perspective:1000px}.carousel-inner>.item.active.right,.carousel-inner>.item.next{left:0;-webkit-transform:translate3d(100%,0,0);transform:translate3d(100%,0,0)}.carousel-inner>.item.active.left,.carousel-inner>.item.prev{left:0;-webkit-transform:translate3d(-100%,0,0);transform:translate3d(-100%,0,0)}.carousel-inner>.item.active,.carousel-inner>.item.next.left,.carousel-inner>.item.prev.right{left:0;-webkit-transform:translate3d(0,0,0);transform:translate3d(0,0,0)}}.carousel-inner>.active,.carousel-inner>.next,.carousel-inner>.prev{display:block}.carousel-inner>.active{left:0}.carousel-inner>.next,.carousel-inner>.prev{position:absolute;top:0;width:100%}.carousel-inner>.next{left:100%}.carousel-inner>.prev{left:-100%}.carousel-inner>.next.left,.carousel-inner>.prev.right{left:0}.carousel-inner>.active.left{left:-100%}.carousel-inner>.active.right{left:100%}.carousel-control{position:absolute;top:0;bottom:0;left:0;width:15%;font-size:20px;color:#fff;text-align:center;text-shadow:0 1px 2px rgba(0,0,0,.6);filter:alpha(opacity=50);opacity:.5}.carousel-control.left{background-image:-webkit-linear-gradient(left,rgba(0,0,0,.5) 0,rgba(0,0,0,.0001) 100%);background-image:-o-linear-gradient(left,rgba(0,0,0,.5) 0,rgba(0,0,0,.0001) 100%);background-image:-webkit-gradient(linear,left top,right top,from(rgba(0,0,0,.5)),to(rgba(0,0,0,.0001)));background-image:linear-gradient(to right,rgba(0,0,0,.5) 0,rgba(0,0,0,.0001) 100%);filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);background-repeat:repeat-x}.carousel-control.right{right:0;left:auto;background-image:-webkit-linear-gradient(left,rgba(0,0,0,.0001) 0,rgba(0,0,0,.5) 100%);background-image:-o-linear-gradient(left,rgba(0,0,0,.0001) 0,rgba(0,0,0,.5) 100%);background-image:-webkit-gradient(linear,left top,right top,from(rgba(0,0,0,.0001)),to(rgba(0,0,0,.5)));background-image:linear-gradient(to right,rgba(0,0,0,.0001) 0,rgba(0,0,0,.5) 100%);filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);background-repeat:repeat-x}.carousel-control:focus,.carousel-control:hover{color:#fff;text-decoration:none;filter:alpha(opacity=90);outline:0;opacity:.9}.carousel-control .glyphicon-chevron-left,.carousel-control .glyphicon-chevron-right,.carousel-control .icon-next,.carousel-control .icon-prev{position:absolute;top:50%;z-index:5;display:inline-block;margin-top:-10px}.carousel-control .glyphicon-chevron-left,.carousel-control .icon-prev{left:50%;margin-left:-10px}.carousel-control .glyphicon-chevron-right,.carousel-control .icon-next{right:50%;margin-right:-10px}.carousel-control .icon-next,.carousel-control .icon-prev{width:20px;height:20px;font-family:serif;line-height:1}.carousel-control .icon-prev:before{content:'\2039'}.carousel-control .icon-next:before{content:'\203a'}.carousel-indicators{position:absolute;bottom:10px;left:50%;z-index:15;width:60%;padding-left:0;margin-left:-30%;text-align:center;list-style:none}.carousel-indicators li{display:inline-block;width:10px;height:10px;margin:1px;text-indent:-999px;cursor:pointer;background-color:#000\9;background-color:rgba(0,0,0,0);border:1px solid #fff;border-radius:10px}.carousel-indicators .active{width:12px;height:12px;margin:0;background-color:#fff}.carousel-caption{position:absolute;right:15%;bottom:20px;left:15%;z-index:10;padding-top:20px;padding-bottom:20px;color:#fff;text-align:center;text-shadow:0 1px 2px rgba(0,0,0,.6)}.carousel-caption .btn{text-shadow:none}@media screen and (min-width:768px){.carousel-control .glyphicon-chevron-left,.carousel-control .glyphicon-chevron-right,.carousel-control .icon-next,.carousel-control .icon-prev{width:30px;height:30px;margin-top:-15px;font-size:30px}.carousel-control .glyphicon-chevron-left,.carousel-control .icon-prev{margin-left:-15px}.carousel-control .glyphicon-chevron-right,.carousel-control .icon-next{margin-right:-15px}.carousel-caption{right:20%;left:20%;padding-bottom:30px}.carousel-indicators{bottom:20px}}.btn-group-vertical>.btn-group:after,.btn-group-vertical>.btn-group:before,.btn-toolbar:after,.btn-toolbar:before,.clearfix:after,.clearfix:before,.container-fluid:after,.container-fluid:before,.container:after,.container:before,.dl-horizontal dd:after,.dl-horizontal dd:before,.form-horizontal .form-group:after,.form-horizontal .form-group:before,.modal-footer:after,.modal-footer:before,.nav:after,.nav:before,.navbar-collapse:after,.navbar-collapse:before,.navbar-header:after,.navbar-header:before,.navbar:after,.navbar:before,.pager:after,.pager:before,.panel-body:after,.panel-body:before,.row:after,.row:before{display:table;content:" "}.btn-group-vertical>.btn-group:after,.btn-toolbar:after,.clearfix:after,.container-fluid:after,.container:after,.dl-horizontal dd:after,.form-horizontal .form-group:after,.modal-footer:after,.nav:after,.navbar-collapse:after,.navbar-header:after,.navbar:after,.pager:after,.panel-body:after,.row:after{clear:both}.center-block{display:block;margin-right:auto;margin-left:auto}.pull-right{float:right!important}.pull-left{float:left!important}.hide{display:none!important}.show{display:block!important}.invisible{visibility:hidden}.text-hide{font:0/0 a;color:transparent;text-shadow:none;background-color:transparent;border:0}.hidden{display:none!important}.affix{position:fixed}@-ms-viewport{width:device-width}.visible-lg,.visible-md,.visible-sm,.visible-xs{display:none!important}.visible-lg-block,.visible-lg-inline,.visible-lg-inline-block,.visible-md-block,.visible-md-inline,.visible-md-inline-block,.visible-sm-block,.visible-sm-inline,.visible-sm-inline-block,.visible-xs-block,.visible-xs-inline,.visible-xs-inline-block{display:none!important}@media (max-width:767px){.visible-xs{display:block!important}table.visible-xs{display:table!important}tr.visible-xs{display:table-row!important}td.visible-xs,th.visible-xs{display:table-cell!important}}@media (max-width:767px){.visible-xs-block{display:block!important}}@media (max-width:767px){.visible-xs-inline{display:inline!important}}@media (max-width:767px){.visible-xs-inline-block{display:inline-block!important}}@media (min-width:768px) and (max-width:991px){.visible-sm{display:block!important}table.visible-sm{display:table!important}tr.visible-sm{display:table-row!important}td.visible-sm,th.visible-sm{display:table-cell!important}}@media (min-width:768px) and (max-width:991px){.visible-sm-block{display:block!important}}@media (min-width:768px) and (max-width:991px){.visible-sm-inline{display:inline!important}}@media (min-width:768px) and (max-width:991px){.visible-sm-inline-block{display:inline-block!important}}@media (min-width:992px) and (max-width:1199px){.visible-md{display:block!important}table.visible-md{display:table!important}tr.visible-md{display:table-row!important}td.visible-md,th.visible-md{display:table-cell!important}}@media (min-width:992px) and (max-width:1199px){.visible-md-block{display:block!important}}@media (min-width:992px) and (max-width:1199px){.visible-md-inline{display:inline!important}}@media (min-width:992px) and (max-width:1199px){.visible-md-inline-block{display:inline-block!important}}@media (min-width:1200px){.visible-lg{display:block!important}table.visible-lg{display:table!important}tr.visible-lg{display:table-row!important}td.visible-lg,th.visible-lg{display:table-cell!important}}@media (min-width:1200px){.visible-lg-block{display:block!important}}@media (min-width:1200px){.visible-lg-inline{display:inline!important}}@media (min-width:1200px){.visible-lg-inline-block{display:inline-block!important}}@media (max-width:767px){.hidden-xs{display:none!important}}@media (min-width:768px) and (max-width:991px){.hidden-sm{display:none!important}}@media (min-width:992px) and (max-width:1199px){.hidden-md{display:none!important}}@media (min-width:1200px){.hidden-lg{display:none!important}}.visible-print{display:none!important}@media print{.visible-print{display:block!important}table.visible-print{display:table!important}tr.visible-print{display:table-row!important}td.visible-print,th.visible-print{display:table-cell!important}}.visible-print-block{display:none!important}@media print{.visible-print-block{display:block!important}}.visible-print-inline{display:none!important}@media print{.visible-print-inline{display:inline!important}}.visible-print-inline-block{display:none!important}@media print{.visible-print-inline-block{display:inline-block!important}}@media print{.hidden-print{display:none!important}}
</style>
<script>/*!
 * Bootstrap v3.3.5 (http://getbootstrap.com)
 * Copyright 2011-2015 Twitter, Inc.
 * Licensed under the MIT license
 */
if("undefined"==typeof jQuery)throw new Error("Bootstrap's JavaScript requires jQuery");+function(a){"use strict";var b=a.fn.jquery.split(" ")[0].split(".");if(b[0]<2&&b[1]<9||1==b[0]&&9==b[1]&&b[2]<1)throw new Error("Bootstrap's JavaScript requires jQuery version 1.9.1 or higher")}(jQuery),+function(a){"use strict";function b(){var a=document.createElement("bootstrap"),b={WebkitTransition:"webkitTransitionEnd",MozTransition:"transitionend",OTransition:"oTransitionEnd otransitionend",transition:"transitionend"};for(var c in b)if(void 0!==a.style[c])return{end:b[c]};return!1}a.fn.emulateTransitionEnd=function(b){var c=!1,d=this;a(this).one("bsTransitionEnd",function(){c=!0});var e=function(){c||a(d).trigger(a.support.transition.end)};return setTimeout(e,b),this},a(function(){a.support.transition=b(),a.support.transition&&(a.event.special.bsTransitionEnd={bindType:a.support.transition.end,delegateType:a.support.transition.end,handle:function(b){return a(b.target).is(this)?b.handleObj.handler.apply(this,arguments):void 0}})})}(jQuery),+function(a){"use strict";function b(b){return this.each(function(){var c=a(this),e=c.data("bs.alert");e||c.data("bs.alert",e=new d(this)),"string"==typeof b&&e[b].call(c)})}var c='[data-dismiss="alert"]',d=function(b){a(b).on("click",c,this.close)};d.VERSION="3.3.5",d.TRANSITION_DURATION=150,d.prototype.close=function(b){function c(){g.detach().trigger("closed.bs.alert").remove()}var e=a(this),f=e.attr("data-target");f||(f=e.attr("href"),f=f&&f.replace(/.*(?=#[^\s]*$)/,""));var g=a(f);b&&b.preventDefault(),g.length||(g=e.closest(".alert")),g.trigger(b=a.Event("close.bs.alert")),b.isDefaultPrevented()||(g.removeClass("in"),a.support.transition&&g.hasClass("fade")?g.one("bsTransitionEnd",c).emulateTransitionEnd(d.TRANSITION_DURATION):c())};var e=a.fn.alert;a.fn.alert=b,a.fn.alert.Constructor=d,a.fn.alert.noConflict=function(){return a.fn.alert=e,this},a(document).on("click.bs.alert.data-api",c,d.prototype.close)}(jQuery),+function(a){"use strict";function b(b){return this.each(function(){var d=a(this),e=d.data("bs.button"),f="object"==typeof b&&b;e||d.data("bs.button",e=new c(this,f)),"toggle"==b?e.toggle():b&&e.setState(b)})}var c=function(b,d){this.$element=a(b),this.options=a.extend({},c.DEFAULTS,d),this.isLoading=!1};c.VERSION="3.3.5",c.DEFAULTS={loadingText:"loading..."},c.prototype.setState=function(b){var c="disabled",d=this.$element,e=d.is("input")?"val":"html",f=d.data();b+="Text",null==f.resetText&&d.data("resetText",d[e]()),setTimeout(a.proxy(function(){d[e](null==f[b]?this.options[b]:f[b]),"loadingText"==b?(this.isLoading=!0,d.addClass(c).attr(c,c)):this.isLoading&&(this.isLoading=!1,d.removeClass(c).removeAttr(c))},this),0)},c.prototype.toggle=function(){var a=!0,b=this.$element.closest('[data-toggle="buttons"]');if(b.length){var c=this.$element.find("input");"radio"==c.prop("type")?(c.prop("checked")&&(a=!1),b.find(".active").removeClass("active"),this.$element.addClass("active")):"checkbox"==c.prop("type")&&(c.prop("checked")!==this.$element.hasClass("active")&&(a=!1),this.$element.toggleClass("active")),c.prop("checked",this.$element.hasClass("active")),a&&c.trigger("change")}else this.$element.attr("aria-pressed",!this.$element.hasClass("active")),this.$element.toggleClass("active")};var d=a.fn.button;a.fn.button=b,a.fn.button.Constructor=c,a.fn.button.noConflict=function(){return a.fn.button=d,this},a(document).on("click.bs.button.data-api",'[data-toggle^="button"]',function(c){var d=a(c.target);d.hasClass("btn")||(d=d.closest(".btn")),b.call(d,"toggle"),a(c.target).is('input[type="radio"]')||a(c.target).is('input[type="checkbox"]')||c.preventDefault()}).on("focus.bs.button.data-api blur.bs.button.data-api",'[data-toggle^="button"]',function(b){a(b.target).closest(".btn").toggleClass("focus",/^focus(in)?$/.test(b.type))})}(jQuery),+function(a){"use strict";function b(b){return this.each(function(){var d=a(this),e=d.data("bs.carousel"),f=a.extend({},c.DEFAULTS,d.data(),"object"==typeof b&&b),g="string"==typeof b?b:f.slide;e||d.data("bs.carousel",e=new c(this,f)),"number"==typeof b?e.to(b):g?e[g]():f.interval&&e.pause().cycle()})}var c=function(b,c){this.$element=a(b),this.$indicators=this.$element.find(".carousel-indicators"),this.options=c,this.paused=null,this.sliding=null,this.interval=null,this.$active=null,this.$items=null,this.options.keyboard&&this.$element.on("keydown.bs.carousel",a.proxy(this.keydown,this)),"hover"==this.options.pause&&!("ontouchstart"in document.documentElement)&&this.$element.on("mouseenter.bs.carousel",a.proxy(this.pause,this)).on("mouseleave.bs.carousel",a.proxy(this.cycle,this))};c.VERSION="3.3.5",c.TRANSITION_DURATION=600,c.DEFAULTS={interval:5e3,pause:"hover",wrap:!0,keyboard:!0},c.prototype.keydown=function(a){if(!/input|textarea/i.test(a.target.tagName)){switch(a.which){case 37:this.prev();break;case 39:this.next();break;default:return}a.preventDefault()}},c.prototype.cycle=function(b){return b||(this.paused=!1),this.interval&&clearInterval(this.interval),this.options.interval&&!this.paused&&(this.interval=setInterval(a.proxy(this.next,this),this.options.interval)),this},c.prototype.getItemIndex=function(a){return this.$items=a.parent().children(".item"),this.$items.index(a||this.$active)},c.prototype.getItemForDirection=function(a,b){var c=this.getItemIndex(b),d="prev"==a&&0===c||"next"==a&&c==this.$items.length-1;if(d&&!this.options.wrap)return b;var e="prev"==a?-1:1,f=(c+e)%this.$items.length;return this.$items.eq(f)},c.prototype.to=function(a){var b=this,c=this.getItemIndex(this.$active=this.$element.find(".item.active"));return a>this.$items.length-1||0>a?void 0:this.sliding?this.$element.one("slid.bs.carousel",function(){b.to(a)}):c==a?this.pause().cycle():this.slide(a>c?"next":"prev",this.$items.eq(a))},c.prototype.pause=function(b){return b||(this.paused=!0),this.$element.find(".next, .prev").length&&a.support.transition&&(this.$element.trigger(a.support.transition.end),this.cycle(!0)),this.interval=clearInterval(this.interval),this},c.prototype.next=function(){return this.sliding?void 0:this.slide("next")},c.prototype.prev=function(){return this.sliding?void 0:this.slide("prev")},c.prototype.slide=function(b,d){var e=this.$element.find(".item.active"),f=d||this.getItemForDirection(b,e),g=this.interval,h="next"==b?"left":"right",i=this;if(f.hasClass("active"))return this.sliding=!1;var j=f[0],k=a.Event("slide.bs.carousel",{relatedTarget:j,direction:h});if(this.$element.trigger(k),!k.isDefaultPrevented()){if(this.sliding=!0,g&&this.pause(),this.$indicators.length){this.$indicators.find(".active").removeClass("active");var l=a(this.$indicators.children()[this.getItemIndex(f)]);l&&l.addClass("active")}var m=a.Event("slid.bs.carousel",{relatedTarget:j,direction:h});return a.support.transition&&this.$element.hasClass("slide")?(f.addClass(b),f[0].offsetWidth,e.addClass(h),f.addClass(h),e.one("bsTransitionEnd",function(){f.removeClass([b,h].join(" ")).addClass("active"),e.removeClass(["active",h].join(" ")),i.sliding=!1,setTimeout(function(){i.$element.trigger(m)},0)}).emulateTransitionEnd(c.TRANSITION_DURATION)):(e.removeClass("active"),f.addClass("active"),this.sliding=!1,this.$element.trigger(m)),g&&this.cycle(),this}};var d=a.fn.carousel;a.fn.carousel=b,a.fn.carousel.Constructor=c,a.fn.carousel.noConflict=function(){return a.fn.carousel=d,this};var e=function(c){var d,e=a(this),f=a(e.attr("data-target")||(d=e.attr("href"))&&d.replace(/.*(?=#[^\s]+$)/,""));if(f.hasClass("carousel")){var g=a.extend({},f.data(),e.data()),h=e.attr("data-slide-to");h&&(g.interval=!1),b.call(f,g),h&&f.data("bs.carousel").to(h),c.preventDefault()}};a(document).on("click.bs.carousel.data-api","[data-slide]",e).on("click.bs.carousel.data-api","[data-slide-to]",e),a(window).on("load",function(){a('[data-ride="carousel"]').each(function(){var c=a(this);b.call(c,c.data())})})}(jQuery),+function(a){"use strict";function b(b){var c,d=b.attr("data-target")||(c=b.attr("href"))&&c.replace(/.*(?=#[^\s]+$)/,"");return a(d)}function c(b){return this.each(function(){var c=a(this),e=c.data("bs.collapse"),f=a.extend({},d.DEFAULTS,c.data(),"object"==typeof b&&b);!e&&f.toggle&&/show|hide/.test(b)&&(f.toggle=!1),e||c.data("bs.collapse",e=new d(this,f)),"string"==typeof b&&e[b]()})}var d=function(b,c){this.$element=a(b),this.options=a.extend({},d.DEFAULTS,c),this.$trigger=a('[data-toggle="collapse"][href="#'+b.id+'"],[data-toggle="collapse"][data-target="#'+b.id+'"]'),this.transitioning=null,this.options.parent?this.$parent=this.getParent():this.addAriaAndCollapsedClass(this.$element,this.$trigger),this.options.toggle&&this.toggle()};d.VERSION="3.3.5",d.TRANSITION_DURATION=350,d.DEFAULTS={toggle:!0},d.prototype.dimension=function(){var a=this.$element.hasClass("width");return a?"width":"height"},d.prototype.show=function(){if(!this.transitioning&&!this.$element.hasClass("in")){var b,e=this.$parent&&this.$parent.children(".panel").children(".in, .collapsing");if(!(e&&e.length&&(b=e.data("bs.collapse"),b&&b.transitioning))){var f=a.Event("show.bs.collapse");if(this.$element.trigger(f),!f.isDefaultPrevented()){e&&e.length&&(c.call(e,"hide"),b||e.data("bs.collapse",null));var g=this.dimension();this.$element.removeClass("collapse").addClass("collapsing")[g](0).attr("aria-expanded",!0),this.$trigger.removeClass("collapsed").attr("aria-expanded",!0),this.transitioning=1;var h=function(){this.$element.removeClass("collapsing").addClass("collapse in")[g](""),this.transitioning=0,this.$element.trigger("shown.bs.collapse")};if(!a.support.transition)return h.call(this);var i=a.camelCase(["scroll",g].join("-"));this.$element.one("bsTransitionEnd",a.proxy(h,this)).emulateTransitionEnd(d.TRANSITION_DURATION)[g](this.$element[0][i])}}}},d.prototype.hide=function(){if(!this.transitioning&&this.$element.hasClass("in")){var b=a.Event("hide.bs.collapse");if(this.$element.trigger(b),!b.isDefaultPrevented()){var c=this.dimension();this.$element[c](this.$element[c]())[0].offsetHeight,this.$element.addClass("collapsing").removeClass("collapse in").attr("aria-expanded",!1),this.$trigger.addClass("collapsed").attr("aria-expanded",!1),this.transitioning=1;var e=function(){this.transitioning=0,this.$element.removeClass("collapsing").addClass("collapse").trigger("hidden.bs.collapse")};return a.support.transition?void this.$element[c](0).one("bsTransitionEnd",a.proxy(e,this)).emulateTransitionEnd(d.TRANSITION_DURATION):e.call(this)}}},d.prototype.toggle=function(){this[this.$element.hasClass("in")?"hide":"show"]()},d.prototype.getParent=function(){return a(this.options.parent).find('[data-toggle="collapse"][data-parent="'+this.options.parent+'"]').each(a.proxy(function(c,d){var e=a(d);this.addAriaAndCollapsedClass(b(e),e)},this)).end()},d.prototype.addAriaAndCollapsedClass=function(a,b){var c=a.hasClass("in");a.attr("aria-expanded",c),b.toggleClass("collapsed",!c).attr("aria-expanded",c)};var e=a.fn.collapse;a.fn.collapse=c,a.fn.collapse.Constructor=d,a.fn.collapse.noConflict=function(){return a.fn.collapse=e,this},a(document).on("click.bs.collapse.data-api",'[data-toggle="collapse"]',function(d){var e=a(this);e.attr("data-target")||d.preventDefault();var f=b(e),g=f.data("bs.collapse"),h=g?"toggle":e.data();c.call(f,h)})}(jQuery),+function(a){"use strict";function b(b){var c=b.attr("data-target");c||(c=b.attr("href"),c=c&&/#[A-Za-z]/.test(c)&&c.replace(/.*(?=#[^\s]*$)/,""));var d=c&&a(c);return d&&d.length?d:b.parent()}function c(c){c&&3===c.which||(a(e).remove(),a(f).each(function(){var d=a(this),e=b(d),f={relatedTarget:this};e.hasClass("open")&&(c&&"click"==c.type&&/input|textarea/i.test(c.target.tagName)&&a.contains(e[0],c.target)||(e.trigger(c=a.Event("hide.bs.dropdown",f)),c.isDefaultPrevented()||(d.attr("aria-expanded","false"),e.removeClass("open").trigger("hidden.bs.dropdown",f))))}))}function d(b){return this.each(function(){var c=a(this),d=c.data("bs.dropdown");d||c.data("bs.dropdown",d=new g(this)),"string"==typeof b&&d[b].call(c)})}var e=".dropdown-backdrop",f='[data-toggle="dropdown"]',g=function(b){a(b).on("click.bs.dropdown",this.toggle)};g.VERSION="3.3.5",g.prototype.toggle=function(d){var e=a(this);if(!e.is(".disabled, :disabled")){var f=b(e),g=f.hasClass("open");if(c(),!g){"ontouchstart"in document.documentElement&&!f.closest(".navbar-nav").length&&a(document.createElement("div")).addClass("dropdown-backdrop").insertAfter(a(this)).on("click",c);var h={relatedTarget:this};if(f.trigger(d=a.Event("show.bs.dropdown",h)),d.isDefaultPrevented())return;e.trigger("focus").attr("aria-expanded","true"),f.toggleClass("open").trigger("shown.bs.dropdown",h)}return!1}},g.prototype.keydown=function(c){if(/(38|40|27|32)/.test(c.which)&&!/input|textarea/i.test(c.target.tagName)){var d=a(this);if(c.preventDefault(),c.stopPropagation(),!d.is(".disabled, :disabled")){var e=b(d),g=e.hasClass("open");if(!g&&27!=c.which||g&&27==c.which)return 27==c.which&&e.find(f).trigger("focus"),d.trigger("click");var h=" li:not(.disabled):visible a",i=e.find(".dropdown-menu"+h);if(i.length){var j=i.index(c.target);38==c.which&&j>0&&j--,40==c.which&&j<i.length-1&&j++,~j||(j=0),i.eq(j).trigger("focus")}}}};var h=a.fn.dropdown;a.fn.dropdown=d,a.fn.dropdown.Constructor=g,a.fn.dropdown.noConflict=function(){return a.fn.dropdown=h,this},a(document).on("click.bs.dropdown.data-api",c).on("click.bs.dropdown.data-api",".dropdown form",function(a){a.stopPropagation()}).on("click.bs.dropdown.data-api",f,g.prototype.toggle).on("keydown.bs.dropdown.data-api",f,g.prototype.keydown).on("keydown.bs.dropdown.data-api",".dropdown-menu",g.prototype.keydown)}(jQuery),+function(a){"use strict";function b(b,d){return this.each(function(){var e=a(this),f=e.data("bs.modal"),g=a.extend({},c.DEFAULTS,e.data(),"object"==typeof b&&b);f||e.data("bs.modal",f=new c(this,g)),"string"==typeof b?f[b](d):g.show&&f.show(d)})}var c=function(b,c){this.options=c,this.$body=a(document.body),this.$element=a(b),this.$dialog=this.$element.find(".modal-dialog"),this.$backdrop=null,this.isShown=null,this.originalBodyPad=null,this.scrollbarWidth=0,this.ignoreBackdropClick=!1,this.options.remote&&this.$element.find(".modal-content").load(this.options.remote,a.proxy(function(){this.$element.trigger("loaded.bs.modal")},this))};c.VERSION="3.3.5",c.TRANSITION_DURATION=300,c.BACKDROP_TRANSITION_DURATION=150,c.DEFAULTS={backdrop:!0,keyboard:!0,show:!0},c.prototype.toggle=function(a){return this.isShown?this.hide():this.show(a)},c.prototype.show=function(b){var d=this,e=a.Event("show.bs.modal",{relatedTarget:b});this.$element.trigger(e),this.isShown||e.isDefaultPrevented()||(this.isShown=!0,this.checkScrollbar(),this.setScrollbar(),this.$body.addClass("modal-open"),this.escape(),this.resize(),this.$element.on("click.dismiss.bs.modal",'[data-dismiss="modal"]',a.proxy(this.hide,this)),this.$dialog.on("mousedown.dismiss.bs.modal",function(){d.$element.one("mouseup.dismiss.bs.modal",function(b){a(b.target).is(d.$element)&&(d.ignoreBackdropClick=!0)})}),this.backdrop(function(){var e=a.support.transition&&d.$element.hasClass("fade");d.$element.parent().length||d.$element.appendTo(d.$body),d.$element.show().scrollTop(0),d.adjustDialog(),e&&d.$element[0].offsetWidth,d.$element.addClass("in"),d.enforceFocus();var f=a.Event("shown.bs.modal",{relatedTarget:b});e?d.$dialog.one("bsTransitionEnd",function(){d.$element.trigger("focus").trigger(f)}).emulateTransitionEnd(c.TRANSITION_DURATION):d.$element.trigger("focus").trigger(f)}))},c.prototype.hide=function(b){b&&b.preventDefault(),b=a.Event("hide.bs.modal"),this.$element.trigger(b),this.isShown&&!b.isDefaultPrevented()&&(this.isShown=!1,this.escape(),this.resize(),a(document).off("focusin.bs.modal"),this.$element.removeClass("in").off("click.dismiss.bs.modal").off("mouseup.dismiss.bs.modal"),this.$dialog.off("mousedown.dismiss.bs.modal"),a.support.transition&&this.$element.hasClass("fade")?this.$element.one("bsTransitionEnd",a.proxy(this.hideModal,this)).emulateTransitionEnd(c.TRANSITION_DURATION):this.hideModal())},c.prototype.enforceFocus=function(){a(document).off("focusin.bs.modal").on("focusin.bs.modal",a.proxy(function(a){this.$element[0]===a.target||this.$element.has(a.target).length||this.$element.trigger("focus")},this))},c.prototype.escape=function(){this.isShown&&this.options.keyboard?this.$element.on("keydown.dismiss.bs.modal",a.proxy(function(a){27==a.which&&this.hide()},this)):this.isShown||this.$element.off("keydown.dismiss.bs.modal")},c.prototype.resize=function(){this.isShown?a(window).on("resize.bs.modal",a.proxy(this.handleUpdate,this)):a(window).off("resize.bs.modal")},c.prototype.hideModal=function(){var a=this;this.$element.hide(),this.backdrop(function(){a.$body.removeClass("modal-open"),a.resetAdjustments(),a.resetScrollbar(),a.$element.trigger("hidden.bs.modal")})},c.prototype.removeBackdrop=function(){this.$backdrop&&this.$backdrop.remove(),this.$backdrop=null},c.prototype.backdrop=function(b){var d=this,e=this.$element.hasClass("fade")?"fade":"";if(this.isShown&&this.options.backdrop){var f=a.support.transition&&e;if(this.$backdrop=a(document.createElement("div")).addClass("modal-backdrop "+e).appendTo(this.$body),this.$element.on("click.dismiss.bs.modal",a.proxy(function(a){return this.ignoreBackdropClick?void(this.ignoreBackdropClick=!1):void(a.target===a.currentTarget&&("static"==this.options.backdrop?this.$element[0].focus():this.hide()))},this)),f&&this.$backdrop[0].offsetWidth,this.$backdrop.addClass("in"),!b)return;f?this.$backdrop.one("bsTransitionEnd",b).emulateTransitionEnd(c.BACKDROP_TRANSITION_DURATION):b()}else if(!this.isShown&&this.$backdrop){this.$backdrop.removeClass("in");var g=function(){d.removeBackdrop(),b&&b()};a.support.transition&&this.$element.hasClass("fade")?this.$backdrop.one("bsTransitionEnd",g).emulateTransitionEnd(c.BACKDROP_TRANSITION_DURATION):g()}else b&&b()},c.prototype.handleUpdate=function(){this.adjustDialog()},c.prototype.adjustDialog=function(){var a=this.$element[0].scrollHeight>document.documentElement.clientHeight;this.$element.css({paddingLeft:!this.bodyIsOverflowing&&a?this.scrollbarWidth:"",paddingRight:this.bodyIsOverflowing&&!a?this.scrollbarWidth:""})},c.prototype.resetAdjustments=function(){this.$element.css({paddingLeft:"",paddingRight:""})},c.prototype.checkScrollbar=function(){var a=window.innerWidth;if(!a){var b=document.documentElement.getBoundingClientRect();a=b.right-Math.abs(b.left)}this.bodyIsOverflowing=document.body.clientWidth<a,this.scrollbarWidth=this.measureScrollbar()},c.prototype.setScrollbar=function(){var a=parseInt(this.$body.css("padding-right")||0,10);this.originalBodyPad=document.body.style.paddingRight||"",this.bodyIsOverflowing&&this.$body.css("padding-right",a+this.scrollbarWidth)},c.prototype.resetScrollbar=function(){this.$body.css("padding-right",this.originalBodyPad)},c.prototype.measureScrollbar=function(){var a=document.createElement("div");a.className="modal-scrollbar-measure",this.$body.append(a);var b=a.offsetWidth-a.clientWidth;return this.$body[0].removeChild(a),b};var d=a.fn.modal;a.fn.modal=b,a.fn.modal.Constructor=c,a.fn.modal.noConflict=function(){return a.fn.modal=d,this},a(document).on("click.bs.modal.data-api",'[data-toggle="modal"]',function(c){var d=a(this),e=d.attr("href"),f=a(d.attr("data-target")||e&&e.replace(/.*(?=#[^\s]+$)/,"")),g=f.data("bs.modal")?"toggle":a.extend({remote:!/#/.test(e)&&e},f.data(),d.data());d.is("a")&&c.preventDefault(),f.one("show.bs.modal",function(a){a.isDefaultPrevented()||f.one("hidden.bs.modal",function(){d.is(":visible")&&d.trigger("focus")})}),b.call(f,g,this)})}(jQuery),+function(a){"use strict";function b(b){return this.each(function(){var d=a(this),e=d.data("bs.tooltip"),f="object"==typeof b&&b;(e||!/destroy|hide/.test(b))&&(e||d.data("bs.tooltip",e=new c(this,f)),"string"==typeof b&&e[b]())})}var c=function(a,b){this.type=null,this.options=null,this.enabled=null,this.timeout=null,this.hoverState=null,this.$element=null,this.inState=null,this.init("tooltip",a,b)};c.VERSION="3.3.5",c.TRANSITION_DURATION=150,c.DEFAULTS={animation:!0,placement:"top",selector:!1,template:'<div class="tooltip" role="tooltip"><div class="tooltip-arrow"></div><div class="tooltip-inner"></div></div>',trigger:"hover focus",title:"",delay:0,html:!1,container:!1,viewport:{selector:"body",padding:0}},c.prototype.init=function(b,c,d){if(this.enabled=!0,this.type=b,this.$element=a(c),this.options=this.getOptions(d),this.$viewport=this.options.viewport&&a(a.isFunction(this.options.viewport)?this.options.viewport.call(this,this.$element):this.options.viewport.selector||this.options.viewport),this.inState={click:!1,hover:!1,focus:!1},this.$element[0]instanceof document.constructor&&!this.options.selector)throw new Error("`selector` option must be specified when initializing "+this.type+" on the window.document object!");for(var e=this.options.trigger.split(" "),f=e.length;f--;){var g=e[f];if("click"==g)this.$element.on("click."+this.type,this.options.selector,a.proxy(this.toggle,this));else if("manual"!=g){var h="hover"==g?"mouseenter":"focusin",i="hover"==g?"mouseleave":"focusout";this.$element.on(h+"."+this.type,this.options.selector,a.proxy(this.enter,this)),this.$element.on(i+"."+this.type,this.options.selector,a.proxy(this.leave,this))}}this.options.selector?this._options=a.extend({},this.options,{trigger:"manual",selector:""}):this.fixTitle()},c.prototype.getDefaults=function(){return c.DEFAULTS},c.prototype.getOptions=function(b){return b=a.extend({},this.getDefaults(),this.$element.data(),b),b.delay&&"number"==typeof b.delay&&(b.delay={show:b.delay,hide:b.delay}),b},c.prototype.getDelegateOptions=function(){var b={},c=this.getDefaults();return this._options&&a.each(this._options,function(a,d){c[a]!=d&&(b[a]=d)}),b},c.prototype.enter=function(b){var c=b instanceof this.constructor?b:a(b.currentTarget).data("bs."+this.type);return c||(c=new this.constructor(b.currentTarget,this.getDelegateOptions()),a(b.currentTarget).data("bs."+this.type,c)),b instanceof a.Event&&(c.inState["focusin"==b.type?"focus":"hover"]=!0),c.tip().hasClass("in")||"in"==c.hoverState?void(c.hoverState="in"):(clearTimeout(c.timeout),c.hoverState="in",c.options.delay&&c.options.delay.show?void(c.timeout=setTimeout(function(){"in"==c.hoverState&&c.show()},c.options.delay.show)):c.show())},c.prototype.isInStateTrue=function(){for(var a in this.inState)if(this.inState[a])return!0;return!1},c.prototype.leave=function(b){var c=b instanceof this.constructor?b:a(b.currentTarget).data("bs."+this.type);return c||(c=new this.constructor(b.currentTarget,this.getDelegateOptions()),a(b.currentTarget).data("bs."+this.type,c)),b instanceof a.Event&&(c.inState["focusout"==b.type?"focus":"hover"]=!1),c.isInStateTrue()?void 0:(clearTimeout(c.timeout),c.hoverState="out",c.options.delay&&c.options.delay.hide?void(c.timeout=setTimeout(function(){"out"==c.hoverState&&c.hide()},c.options.delay.hide)):c.hide())},c.prototype.show=function(){var b=a.Event("show.bs."+this.type);if(this.hasContent()&&this.enabled){this.$element.trigger(b);var d=a.contains(this.$element[0].ownerDocument.documentElement,this.$element[0]);if(b.isDefaultPrevented()||!d)return;var e=this,f=this.tip(),g=this.getUID(this.type);this.setContent(),f.attr("id",g),this.$element.attr("aria-describedby",g),this.options.animation&&f.addClass("fade");var h="function"==typeof this.options.placement?this.options.placement.call(this,f[0],this.$element[0]):this.options.placement,i=/\s?auto?\s?/i,j=i.test(h);j&&(h=h.replace(i,"")||"top"),f.detach().css({top:0,left:0,display:"block"}).addClass(h).data("bs."+this.type,this),this.options.container?f.appendTo(this.options.container):f.insertAfter(this.$element),this.$element.trigger("inserted.bs."+this.type);var k=this.getPosition(),l=f[0].offsetWidth,m=f[0].offsetHeight;if(j){var n=h,o=this.getPosition(this.$viewport);h="bottom"==h&&k.bottom+m>o.bottom?"top":"top"==h&&k.top-m<o.top?"bottom":"right"==h&&k.right+l>o.width?"left":"left"==h&&k.left-l<o.left?"right":h,f.removeClass(n).addClass(h)}var p=this.getCalculatedOffset(h,k,l,m);this.applyPlacement(p,h);var q=function(){var a=e.hoverState;e.$element.trigger("shown.bs."+e.type),e.hoverState=null,"out"==a&&e.leave(e)};a.support.transition&&this.$tip.hasClass("fade")?f.one("bsTransitionEnd",q).emulateTransitionEnd(c.TRANSITION_DURATION):q()}},c.prototype.applyPlacement=function(b,c){var d=this.tip(),e=d[0].offsetWidth,f=d[0].offsetHeight,g=parseInt(d.css("margin-top"),10),h=parseInt(d.css("margin-left"),10);isNaN(g)&&(g=0),isNaN(h)&&(h=0),b.top+=g,b.left+=h,a.offset.setOffset(d[0],a.extend({using:function(a){d.css({top:Math.round(a.top),left:Math.round(a.left)})}},b),0),d.addClass("in");var i=d[0].offsetWidth,j=d[0].offsetHeight;"top"==c&&j!=f&&(b.top=b.top+f-j);var k=this.getViewportAdjustedDelta(c,b,i,j);k.left?b.left+=k.left:b.top+=k.top;var l=/top|bottom/.test(c),m=l?2*k.left-e+i:2*k.top-f+j,n=l?"offsetWidth":"offsetHeight";d.offset(b),this.replaceArrow(m,d[0][n],l)},c.prototype.replaceArrow=function(a,b,c){this.arrow().css(c?"left":"top",50*(1-a/b)+"%").css(c?"top":"left","")},c.prototype.setContent=function(){var a=this.tip(),b=this.getTitle();a.find(".tooltip-inner")[this.options.html?"html":"text"](b),a.removeClass("fade in top bottom left right")},c.prototype.hide=function(b){function d(){"in"!=e.hoverState&&f.detach(),e.$element.removeAttr("aria-describedby").trigger("hidden.bs."+e.type),b&&b()}var e=this,f=a(this.$tip),g=a.Event("hide.bs."+this.type);return this.$element.trigger(g),g.isDefaultPrevented()?void 0:(f.removeClass("in"),a.support.transition&&f.hasClass("fade")?f.one("bsTransitionEnd",d).emulateTransitionEnd(c.TRANSITION_DURATION):d(),this.hoverState=null,this)},c.prototype.fixTitle=function(){var a=this.$element;(a.attr("title")||"string"!=typeof a.attr("data-original-title"))&&a.attr("data-original-title",a.attr("title")||"").attr("title","")},c.prototype.hasContent=function(){return this.getTitle()},c.prototype.getPosition=function(b){b=b||this.$element;var c=b[0],d="BODY"==c.tagName,e=c.getBoundingClientRect();null==e.width&&(e=a.extend({},e,{width:e.right-e.left,height:e.bottom-e.top}));var f=d?{top:0,left:0}:b.offset(),g={scroll:d?document.documentElement.scrollTop||document.body.scrollTop:b.scrollTop()},h=d?{width:a(window).width(),height:a(window).height()}:null;return a.extend({},e,g,h,f)},c.prototype.getCalculatedOffset=function(a,b,c,d){return"bottom"==a?{top:b.top+b.height,left:b.left+b.width/2-c/2}:"top"==a?{top:b.top-d,left:b.left+b.width/2-c/2}:"left"==a?{top:b.top+b.height/2-d/2,left:b.left-c}:{top:b.top+b.height/2-d/2,left:b.left+b.width}},c.prototype.getViewportAdjustedDelta=function(a,b,c,d){var e={top:0,left:0};if(!this.$viewport)return e;var f=this.options.viewport&&this.options.viewport.padding||0,g=this.getPosition(this.$viewport);if(/right|left/.test(a)){var h=b.top-f-g.scroll,i=b.top+f-g.scroll+d;h<g.top?e.top=g.top-h:i>g.top+g.height&&(e.top=g.top+g.height-i)}else{var j=b.left-f,k=b.left+f+c;j<g.left?e.left=g.left-j:k>g.right&&(e.left=g.left+g.width-k)}return e},c.prototype.getTitle=function(){var a,b=this.$element,c=this.options;return a=b.attr("data-original-title")||("function"==typeof c.title?c.title.call(b[0]):c.title)},c.prototype.getUID=function(a){do a+=~~(1e6*Math.random());while(document.getElementById(a));return a},c.prototype.tip=function(){if(!this.$tip&&(this.$tip=a(this.options.template),1!=this.$tip.length))throw new Error(this.type+" `template` option must consist of exactly 1 top-level element!");return this.$tip},c.prototype.arrow=function(){return this.$arrow=this.$arrow||this.tip().find(".tooltip-arrow")},c.prototype.enable=function(){this.enabled=!0},c.prototype.disable=function(){this.enabled=!1},c.prototype.toggleEnabled=function(){this.enabled=!this.enabled},c.prototype.toggle=function(b){var c=this;b&&(c=a(b.currentTarget).data("bs."+this.type),c||(c=new this.constructor(b.currentTarget,this.getDelegateOptions()),a(b.currentTarget).data("bs."+this.type,c))),b?(c.inState.click=!c.inState.click,c.isInStateTrue()?c.enter(c):c.leave(c)):c.tip().hasClass("in")?c.leave(c):c.enter(c)},c.prototype.destroy=function(){var a=this;clearTimeout(this.timeout),this.hide(function(){a.$element.off("."+a.type).removeData("bs."+a.type),a.$tip&&a.$tip.detach(),a.$tip=null,a.$arrow=null,a.$viewport=null})};var d=a.fn.tooltip;a.fn.tooltip=b,a.fn.tooltip.Constructor=c,a.fn.tooltip.noConflict=function(){return a.fn.tooltip=d,this}}(jQuery),+function(a){"use strict";function b(b){return this.each(function(){var d=a(this),e=d.data("bs.popover"),f="object"==typeof b&&b;(e||!/destroy|hide/.test(b))&&(e||d.data("bs.popover",e=new c(this,f)),"string"==typeof b&&e[b]())})}var c=function(a,b){this.init("popover",a,b)};if(!a.fn.tooltip)throw new Error("Popover requires tooltip.js");c.VERSION="3.3.5",c.DEFAULTS=a.extend({},a.fn.tooltip.Constructor.DEFAULTS,{placement:"right",trigger:"click",content:"",template:'<div class="popover" role="tooltip"><div class="arrow"></div><h3 class="popover-title"></h3><div class="popover-content"></div></div>'}),c.prototype=a.extend({},a.fn.tooltip.Constructor.prototype),c.prototype.constructor=c,c.prototype.getDefaults=function(){return c.DEFAULTS},c.prototype.setContent=function(){var a=this.tip(),b=this.getTitle(),c=this.getContent();a.find(".popover-title")[this.options.html?"html":"text"](b),a.find(".popover-content").children().detach().end()[this.options.html?"string"==typeof c?"html":"append":"text"](c),a.removeClass("fade top bottom left right in"),a.find(".popover-title").html()||a.find(".popover-title").hide()},c.prototype.hasContent=function(){return this.getTitle()||this.getContent()},c.prototype.getContent=function(){var a=this.$element,b=this.options;return a.attr("data-content")||("function"==typeof b.content?b.content.call(a[0]):b.content)},c.prototype.arrow=function(){return this.$arrow=this.$arrow||this.tip().find(".arrow")};var d=a.fn.popover;a.fn.popover=b,a.fn.popover.Constructor=c,a.fn.popover.noConflict=function(){return a.fn.popover=d,this}}(jQuery),+function(a){"use strict";function b(c,d){this.$body=a(document.body),this.$scrollElement=a(a(c).is(document.body)?window:c),this.options=a.extend({},b.DEFAULTS,d),this.selector=(this.options.target||"")+" .nav li > a",this.offsets=[],this.targets=[],this.activeTarget=null,this.scrollHeight=0,this.$scrollElement.on("scroll.bs.scrollspy",a.proxy(this.process,this)),this.refresh(),this.process()}function c(c){return this.each(function(){var d=a(this),e=d.data("bs.scrollspy"),f="object"==typeof c&&c;e||d.data("bs.scrollspy",e=new b(this,f)),"string"==typeof c&&e[c]()})}b.VERSION="3.3.5",b.DEFAULTS={offset:10},b.prototype.getScrollHeight=function(){return this.$scrollElement[0].scrollHeight||Math.max(this.$body[0].scrollHeight,document.documentElement.scrollHeight)},b.prototype.refresh=function(){var b=this,c="offset",d=0;this.offsets=[],this.targets=[],this.scrollHeight=this.getScrollHeight(),a.isWindow(this.$scrollElement[0])||(c="position",d=this.$scrollElement.scrollTop()),this.$body.find(this.selector).map(function(){var b=a(this),e=b.data("target")||b.attr("href"),f=/^#./.test(e)&&a(e);return f&&f.length&&f.is(":visible")&&[[f[c]().top+d,e]]||null}).sort(function(a,b){return a[0]-b[0]}).each(function(){b.offsets.push(this[0]),b.targets.push(this[1])})},b.prototype.process=function(){var a,b=this.$scrollElement.scrollTop()+this.options.offset,c=this.getScrollHeight(),d=this.options.offset+c-this.$scrollElement.height(),e=this.offsets,f=this.targets,g=this.activeTarget;if(this.scrollHeight!=c&&this.refresh(),b>=d)return g!=(a=f[f.length-1])&&this.activate(a);if(g&&b<e[0])return this.activeTarget=null,this.clear();for(a=e.length;a--;)g!=f[a]&&b>=e[a]&&(void 0===e[a+1]||b<e[a+1])&&this.activate(f[a])},b.prototype.activate=function(b){this.activeTarget=b,this.clear();var c=this.selector+'[data-target="'+b+'"],'+this.selector+'[href="'+b+'"]',d=a(c).parents("li").addClass("active");d.parent(".dropdown-menu").length&&(d=d.closest("li.dropdown").addClass("active")),
d.trigger("activate.bs.scrollspy")},b.prototype.clear=function(){a(this.selector).parentsUntil(this.options.target,".active").removeClass("active")};var d=a.fn.scrollspy;a.fn.scrollspy=c,a.fn.scrollspy.Constructor=b,a.fn.scrollspy.noConflict=function(){return a.fn.scrollspy=d,this},a(window).on("load.bs.scrollspy.data-api",function(){a('[data-spy="scroll"]').each(function(){var b=a(this);c.call(b,b.data())})})}(jQuery),+function(a){"use strict";function b(b){return this.each(function(){var d=a(this),e=d.data("bs.tab");e||d.data("bs.tab",e=new c(this)),"string"==typeof b&&e[b]()})}var c=function(b){this.element=a(b)};c.VERSION="3.3.5",c.TRANSITION_DURATION=150,c.prototype.show=function(){var b=this.element,c=b.closest("ul:not(.dropdown-menu)"),d=b.data("target");if(d||(d=b.attr("href"),d=d&&d.replace(/.*(?=#[^\s]*$)/,"")),!b.parent("li").hasClass("active")){var e=c.find(".active:last a"),f=a.Event("hide.bs.tab",{relatedTarget:b[0]}),g=a.Event("show.bs.tab",{relatedTarget:e[0]});if(e.trigger(f),b.trigger(g),!g.isDefaultPrevented()&&!f.isDefaultPrevented()){var h=a(d);this.activate(b.closest("li"),c),this.activate(h,h.parent(),function(){e.trigger({type:"hidden.bs.tab",relatedTarget:b[0]}),b.trigger({type:"shown.bs.tab",relatedTarget:e[0]})})}}},c.prototype.activate=function(b,d,e){function f(){g.removeClass("active").find("> .dropdown-menu > .active").removeClass("active").end().find('[data-toggle="tab"]').attr("aria-expanded",!1),b.addClass("active").find('[data-toggle="tab"]').attr("aria-expanded",!0),h?(b[0].offsetWidth,b.addClass("in")):b.removeClass("fade"),b.parent(".dropdown-menu").length&&b.closest("li.dropdown").addClass("active").end().find('[data-toggle="tab"]').attr("aria-expanded",!0),e&&e()}var g=d.find("> .active"),h=e&&a.support.transition&&(g.length&&g.hasClass("fade")||!!d.find("> .fade").length);g.length&&h?g.one("bsTransitionEnd",f).emulateTransitionEnd(c.TRANSITION_DURATION):f(),g.removeClass("in")};var d=a.fn.tab;a.fn.tab=b,a.fn.tab.Constructor=c,a.fn.tab.noConflict=function(){return a.fn.tab=d,this};var e=function(c){c.preventDefault(),b.call(a(this),"show")};a(document).on("click.bs.tab.data-api",'[data-toggle="tab"]',e).on("click.bs.tab.data-api",'[data-toggle="pill"]',e)}(jQuery),+function(a){"use strict";function b(b){return this.each(function(){var d=a(this),e=d.data("bs.affix"),f="object"==typeof b&&b;e||d.data("bs.affix",e=new c(this,f)),"string"==typeof b&&e[b]()})}var c=function(b,d){this.options=a.extend({},c.DEFAULTS,d),this.$target=a(this.options.target).on("scroll.bs.affix.data-api",a.proxy(this.checkPosition,this)).on("click.bs.affix.data-api",a.proxy(this.checkPositionWithEventLoop,this)),this.$element=a(b),this.affixed=null,this.unpin=null,this.pinnedOffset=null,this.checkPosition()};c.VERSION="3.3.5",c.RESET="affix affix-top affix-bottom",c.DEFAULTS={offset:0,target:window},c.prototype.getState=function(a,b,c,d){var e=this.$target.scrollTop(),f=this.$element.offset(),g=this.$target.height();if(null!=c&&"top"==this.affixed)return c>e?"top":!1;if("bottom"==this.affixed)return null!=c?e+this.unpin<=f.top?!1:"bottom":a-d>=e+g?!1:"bottom";var h=null==this.affixed,i=h?e:f.top,j=h?g:b;return null!=c&&c>=e?"top":null!=d&&i+j>=a-d?"bottom":!1},c.prototype.getPinnedOffset=function(){if(this.pinnedOffset)return this.pinnedOffset;this.$element.removeClass(c.RESET).addClass("affix");var a=this.$target.scrollTop(),b=this.$element.offset();return this.pinnedOffset=b.top-a},c.prototype.checkPositionWithEventLoop=function(){setTimeout(a.proxy(this.checkPosition,this),1)},c.prototype.checkPosition=function(){if(this.$element.is(":visible")){var b=this.$element.height(),d=this.options.offset,e=d.top,f=d.bottom,g=Math.max(a(document).height(),a(document.body).height());"object"!=typeof d&&(f=e=d),"function"==typeof e&&(e=d.top(this.$element)),"function"==typeof f&&(f=d.bottom(this.$element));var h=this.getState(g,b,e,f);if(this.affixed!=h){null!=this.unpin&&this.$element.css("top","");var i="affix"+(h?"-"+h:""),j=a.Event(i+".bs.affix");if(this.$element.trigger(j),j.isDefaultPrevented())return;this.affixed=h,this.unpin="bottom"==h?this.getPinnedOffset():null,this.$element.removeClass(c.RESET).addClass(i).trigger(i.replace("affix","affixed")+".bs.affix")}"bottom"==h&&this.$element.offset({top:g-b-f})}};var d=a.fn.affix;a.fn.affix=b,a.fn.affix.Constructor=c,a.fn.affix.noConflict=function(){return a.fn.affix=d,this},a(window).on("load",function(){a('[data-spy="affix"]').each(function(){var c=a(this),d=c.data();d.offset=d.offset||{},null!=d.offsetBottom&&(d.offset.bottom=d.offsetBottom),null!=d.offsetTop&&(d.offset.top=d.offsetTop),b.call(c,d)})})}(jQuery);</script>
<script>/**
* @preserve HTML5 Shiv 3.7.2 | @afarkas @jdalton @jon_neal @rem | MIT/GPL2 Licensed
*/
// Only run this code in IE 8
if (!!window.navigator.userAgent.match("MSIE 8")) {
!function(a,b){function c(a,b){var c=a.createElement("p"),d=a.getElementsByTagName("head")[0]||a.documentElement;return c.innerHTML="x<style>"+b+"</style>",d.insertBefore(c.lastChild,d.firstChild)}function d(){var a=t.elements;return"string"==typeof a?a.split(" "):a}function e(a,b){var c=t.elements;"string"!=typeof c&&(c=c.join(" ")),"string"!=typeof a&&(a=a.join(" ")),t.elements=c+" "+a,j(b)}function f(a){var b=s[a[q]];return b||(b={},r++,a[q]=r,s[r]=b),b}function g(a,c,d){if(c||(c=b),l)return c.createElement(a);d||(d=f(c));var e;return e=d.cache[a]?d.cache[a].cloneNode():p.test(a)?(d.cache[a]=d.createElem(a)).cloneNode():d.createElem(a),!e.canHaveChildren||o.test(a)||e.tagUrn?e:d.frag.appendChild(e)}function h(a,c){if(a||(a=b),l)return a.createDocumentFragment();c=c||f(a);for(var e=c.frag.cloneNode(),g=0,h=d(),i=h.length;i>g;g++)e.createElement(h[g]);return e}function i(a,b){b.cache||(b.cache={},b.createElem=a.createElement,b.createFrag=a.createDocumentFragment,b.frag=b.createFrag()),a.createElement=function(c){return t.shivMethods?g(c,a,b):b.createElem(c)},a.createDocumentFragment=Function("h,f","return function(){var n=f.cloneNode(),c=n.createElement;h.shivMethods&&("+d().join().replace(/[\w\-:]+/g,function(a){return b.createElem(a),b.frag.createElement(a),'c("'+a+'")'})+");return n}")(t,b.frag)}function j(a){a||(a=b);var d=f(a);return!t.shivCSS||k||d.hasCSS||(d.hasCSS=!!c(a,"article,aside,dialog,figcaption,figure,footer,header,hgroup,main,nav,section{display:block}mark{background:#FF0;color:#000}template{display:none}")),l||i(a,d),a}var k,l,m="3.7.2",n=a.html5||{},o=/^<|^(?:button|map|select|textarea|object|iframe|option|optgroup)$/i,p=/^(?:a|b|code|div|fieldset|h1|h2|h3|h4|h5|h6|i|label|li|ol|p|q|span|strong|style|table|tbody|td|th|tr|ul)$/i,q="_html5shiv",r=0,s={};!function(){try{var a=b.createElement("a");a.innerHTML="<xyz></xyz>",k="hidden"in a,l=1==a.childNodes.length||function(){b.createElement("a");var a=b.createDocumentFragment();return"undefined"==typeof a.cloneNode||"undefined"==typeof a.createDocumentFragment||"undefined"==typeof a.createElement}()}catch(c){k=!0,l=!0}}();var t={elements:n.elements||"abbr article aside audio bdi canvas data datalist details dialog figcaption figure footer header hgroup main mark meter nav output picture progress section summary template time video",version:m,shivCSS:n.shivCSS!==!1,supportsUnknownElements:l,shivMethods:n.shivMethods!==!1,type:"default",shivDocument:j,createElement:g,createDocumentFragment:h,addElements:e};a.html5=t,j(b)}(this,document);
};
</script>
<script>/*! Respond.js v1.4.2: min/max-width media query polyfill * Copyright 2013 Scott Jehl
 * Licensed under https://github.com/scottjehl/Respond/blob/master/LICENSE-MIT
 *  */

// Only run this code in IE 8
if (!!window.navigator.userAgent.match("MSIE 8")) {
!function(a){"use strict";a.matchMedia=a.matchMedia||function(a){var b,c=a.documentElement,d=c.firstElementChild||c.firstChild,e=a.createElement("body"),f=a.createElement("div");return f.id="mq-test-1",f.style.cssText="position:absolute;top:-100em",e.style.background="none",e.appendChild(f),function(a){return f.innerHTML='&shy;<style media="'+a+'"> #mq-test-1 { width: 42px; }</style>',c.insertBefore(e,d),b=42===f.offsetWidth,c.removeChild(e),{matches:b,media:a}}}(a.document)}(this),function(a){"use strict";function b(){u(!0)}var c={};a.respond=c,c.update=function(){};var d=[],e=function(){var b=!1;try{b=new a.XMLHttpRequest}catch(c){b=new a.ActiveXObject("Microsoft.XMLHTTP")}return function(){return b}}(),f=function(a,b){var c=e();c&&(c.open("GET",a,!0),c.onreadystatechange=function(){4!==c.readyState||200!==c.status&&304!==c.status||b(c.responseText)},4!==c.readyState&&c.send(null))};if(c.ajax=f,c.queue=d,c.regex={media:/@media[^\{]+\{([^\{\}]*\{[^\}\{]*\})+/gi,keyframes:/@(?:\-(?:o|moz|webkit)\-)?keyframes[^\{]+\{(?:[^\{\}]*\{[^\}\{]*\})+[^\}]*\}/gi,urls:/(url\()['"]?([^\/\)'"][^:\)'"]+)['"]?(\))/g,findStyles:/@media *([^\{]+)\{([\S\s]+?)$/,only:/(only\s+)?([a-zA-Z]+)\s?/,minw:/\([\s]*min\-width\s*:[\s]*([\s]*[0-9\.]+)(px|em)[\s]*\)/,maxw:/\([\s]*max\-width\s*:[\s]*([\s]*[0-9\.]+)(px|em)[\s]*\)/},c.mediaQueriesSupported=a.matchMedia&&null!==a.matchMedia("only all")&&a.matchMedia("only all").matches,!c.mediaQueriesSupported){var g,h,i,j=a.document,k=j.documentElement,l=[],m=[],n=[],o={},p=30,q=j.getElementsByTagName("head")[0]||k,r=j.getElementsByTagName("base")[0],s=q.getElementsByTagName("link"),t=function(){var a,b=j.createElement("div"),c=j.body,d=k.style.fontSize,e=c&&c.style.fontSize,f=!1;return b.style.cssText="position:absolute;font-size:1em;width:1em",c||(c=f=j.createElement("body"),c.style.background="none"),k.style.fontSize="100%",c.style.fontSize="100%",c.appendChild(b),f&&k.insertBefore(c,k.firstChild),a=b.offsetWidth,f?k.removeChild(c):c.removeChild(b),k.style.fontSize=d,e&&(c.style.fontSize=e),a=i=parseFloat(a)},u=function(b){var c="clientWidth",d=k[c],e="CSS1Compat"===j.compatMode&&d||j.body[c]||d,f={},o=s[s.length-1],r=(new Date).getTime();if(b&&g&&p>r-g)return a.clearTimeout(h),h=a.setTimeout(u,p),void 0;g=r;for(var v in l)if(l.hasOwnProperty(v)){var w=l[v],x=w.minw,y=w.maxw,z=null===x,A=null===y,B="em";x&&(x=parseFloat(x)*(x.indexOf(B)>-1?i||t():1)),y&&(y=parseFloat(y)*(y.indexOf(B)>-1?i||t():1)),w.hasquery&&(z&&A||!(z||e>=x)||!(A||y>=e))||(f[w.media]||(f[w.media]=[]),f[w.media].push(m[w.rules]))}for(var C in n)n.hasOwnProperty(C)&&n[C]&&n[C].parentNode===q&&q.removeChild(n[C]);n.length=0;for(var D in f)if(f.hasOwnProperty(D)){var E=j.createElement("style"),F=f[D].join("\n");E.type="text/css",E.media=D,q.insertBefore(E,o.nextSibling),E.styleSheet?E.styleSheet.cssText=F:E.appendChild(j.createTextNode(F)),n.push(E)}},v=function(a,b,d){var e=a.replace(c.regex.keyframes,"").match(c.regex.media),f=e&&e.length||0;b=b.substring(0,b.lastIndexOf("/"));var g=function(a){return a.replace(c.regex.urls,"$1"+b+"$2$3")},h=!f&&d;b.length&&(b+="/"),h&&(f=1);for(var i=0;f>i;i++){var j,k,n,o;h?(j=d,m.push(g(a))):(j=e[i].match(c.regex.findStyles)&&RegExp.$1,m.push(RegExp.$2&&g(RegExp.$2))),n=j.split(","),o=n.length;for(var p=0;o>p;p++)k=n[p],l.push({media:k.split("(")[0].match(c.regex.only)&&RegExp.$2||"all",rules:m.length-1,hasquery:k.indexOf("(")>-1,minw:k.match(c.regex.minw)&&parseFloat(RegExp.$1)+(RegExp.$2||""),maxw:k.match(c.regex.maxw)&&parseFloat(RegExp.$1)+(RegExp.$2||"")})}u()},w=function(){if(d.length){var b=d.shift();f(b.href,function(c){v(c,b.href,b.media),o[b.href]=!0,a.setTimeout(function(){w()},0)})}},x=function(){for(var b=0;b<s.length;b++){var c=s[b],e=c.href,f=c.media,g=c.rel&&"stylesheet"===c.rel.toLowerCase();e&&g&&!o[e]&&(c.styleSheet&&c.styleSheet.rawCssText?(v(c.styleSheet.rawCssText,e,f),o[e]=!0):(!/^([a-zA-Z:]*\/\/)/.test(e)&&!r||e.replace(RegExp.$1,"").split("/")[0]===a.location.host)&&("//"===e.substring(0,2)&&(e=a.location.protocol+e),d.push({href:e,media:f})))}w()};x(),c.update=x,c.getEmValue=t,a.addEventListener?a.addEventListener("resize",b,!1):a.attachEvent&&a.attachEvent("onresize",b)}}(this);
};
</script>
<style>h1 {font-size: 34px;}
h1.title {font-size: 38px;}
h2 {font-size: 30px;}
h3 {font-size: 24px;}
h4 {font-size: 18px;}
h5 {font-size: 16px;}
h6 {font-size: 12px;}
code {color: inherit; background-color: rgba(0, 0, 0, 0.04);}
pre:not([class]) { background-color: white }</style>
<script>/*! jQuery UI - v1.11.4 - 2016-01-05
* http://jqueryui.com
* Includes: core.js, widget.js, mouse.js, position.js, draggable.js, droppable.js, resizable.js, selectable.js, sortable.js, accordion.js, autocomplete.js, button.js, dialog.js, menu.js, progressbar.js, selectmenu.js, slider.js, spinner.js, tabs.js, tooltip.js, effect.js, effect-blind.js, effect-bounce.js, effect-clip.js, effect-drop.js, effect-explode.js, effect-fade.js, effect-fold.js, effect-highlight.js, effect-puff.js, effect-pulsate.js, effect-scale.js, effect-shake.js, effect-size.js, effect-slide.js, effect-transfer.js
* Copyright jQuery Foundation and other contributors; Licensed MIT */

(function(e){"function"==typeof define&&define.amd?define(["jquery"],e):e(jQuery)})(function(e){function t(t,s){var n,a,o,r=t.nodeName.toLowerCase();return"area"===r?(n=t.parentNode,a=n.name,t.href&&a&&"map"===n.nodeName.toLowerCase()?(o=e("img[usemap='#"+a+"']")[0],!!o&&i(o)):!1):(/^(input|select|textarea|button|object)$/.test(r)?!t.disabled:"a"===r?t.href||s:s)&&i(t)}function i(t){return e.expr.filters.visible(t)&&!e(t).parents().addBack().filter(function(){return"hidden"===e.css(this,"visibility")}).length}function s(e){return function(){var t=this.element.val();e.apply(this,arguments),this._refresh(),t!==this.element.val()&&this._trigger("change")}}e.ui=e.ui||{},e.extend(e.ui,{version:"1.11.4",keyCode:{BACKSPACE:8,COMMA:188,DELETE:46,DOWN:40,END:35,ENTER:13,ESCAPE:27,HOME:36,LEFT:37,PAGE_DOWN:34,PAGE_UP:33,PERIOD:190,RIGHT:39,SPACE:32,TAB:9,UP:38}}),e.fn.extend({scrollParent:function(t){var i=this.css("position"),s="absolute"===i,n=t?/(auto|scroll|hidden)/:/(auto|scroll)/,a=this.parents().filter(function(){var t=e(this);return s&&"static"===t.css("position")?!1:n.test(t.css("overflow")+t.css("overflow-y")+t.css("overflow-x"))}).eq(0);return"fixed"!==i&&a.length?a:e(this[0].ownerDocument||document)},uniqueId:function(){var e=0;return function(){return this.each(function(){this.id||(this.id="ui-id-"+ ++e)})}}(),removeUniqueId:function(){return this.each(function(){/^ui-id-\d+$/.test(this.id)&&e(this).removeAttr("id")})}}),e.extend(e.expr[":"],{data:e.expr.createPseudo?e.expr.createPseudo(function(t){return function(i){return!!e.data(i,t)}}):function(t,i,s){return!!e.data(t,s[3])},focusable:function(i){return t(i,!isNaN(e.attr(i,"tabindex")))},tabbable:function(i){var s=e.attr(i,"tabindex"),n=isNaN(s);return(n||s>=0)&&t(i,!n)}}),e("<a>").outerWidth(1).jquery||e.each(["Width","Height"],function(t,i){function s(t,i,s,a){return e.each(n,function(){i-=parseFloat(e.css(t,"padding"+this))||0,s&&(i-=parseFloat(e.css(t,"border"+this+"Width"))||0),a&&(i-=parseFloat(e.css(t,"margin"+this))||0)}),i}var n="Width"===i?["Left","Right"]:["Top","Bottom"],a=i.toLowerCase(),o={innerWidth:e.fn.innerWidth,innerHeight:e.fn.innerHeight,outerWidth:e.fn.outerWidth,outerHeight:e.fn.outerHeight};e.fn["inner"+i]=function(t){return void 0===t?o["inner"+i].call(this):this.each(function(){e(this).css(a,s(this,t)+"px")})},e.fn["outer"+i]=function(t,n){return"number"!=typeof t?o["outer"+i].call(this,t):this.each(function(){e(this).css(a,s(this,t,!0,n)+"px")})}}),e.fn.addBack||(e.fn.addBack=function(e){return this.add(null==e?this.prevObject:this.prevObject.filter(e))}),e("<a>").data("a-b","a").removeData("a-b").data("a-b")&&(e.fn.removeData=function(t){return function(i){return arguments.length?t.call(this,e.camelCase(i)):t.call(this)}}(e.fn.removeData)),e.ui.ie=!!/msie [\w.]+/.exec(navigator.userAgent.toLowerCase()),e.fn.extend({focus:function(t){return function(i,s){return"number"==typeof i?this.each(function(){var t=this;setTimeout(function(){e(t).focus(),s&&s.call(t)},i)}):t.apply(this,arguments)}}(e.fn.focus),disableSelection:function(){var e="onselectstart"in document.createElement("div")?"selectstart":"mousedown";return function(){return this.bind(e+".ui-disableSelection",function(e){e.preventDefault()})}}(),enableSelection:function(){return this.unbind(".ui-disableSelection")},zIndex:function(t){if(void 0!==t)return this.css("zIndex",t);if(this.length)for(var i,s,n=e(this[0]);n.length&&n[0]!==document;){if(i=n.css("position"),("absolute"===i||"relative"===i||"fixed"===i)&&(s=parseInt(n.css("zIndex"),10),!isNaN(s)&&0!==s))return s;n=n.parent()}return 0}}),e.ui.plugin={add:function(t,i,s){var n,a=e.ui[t].prototype;for(n in s)a.plugins[n]=a.plugins[n]||[],a.plugins[n].push([i,s[n]])},call:function(e,t,i,s){var n,a=e.plugins[t];if(a&&(s||e.element[0].parentNode&&11!==e.element[0].parentNode.nodeType))for(n=0;a.length>n;n++)e.options[a[n][0]]&&a[n][1].apply(e.element,i)}};var n=0,a=Array.prototype.slice;e.cleanData=function(t){return function(i){var s,n,a;for(a=0;null!=(n=i[a]);a++)try{s=e._data(n,"events"),s&&s.remove&&e(n).triggerHandler("remove")}catch(o){}t(i)}}(e.cleanData),e.widget=function(t,i,s){var n,a,o,r,h={},l=t.split(".")[0];return t=t.split(".")[1],n=l+"-"+t,s||(s=i,i=e.Widget),e.expr[":"][n.toLowerCase()]=function(t){return!!e.data(t,n)},e[l]=e[l]||{},a=e[l][t],o=e[l][t]=function(e,t){return this._createWidget?(arguments.length&&this._createWidget(e,t),void 0):new o(e,t)},e.extend(o,a,{version:s.version,_proto:e.extend({},s),_childConstructors:[]}),r=new i,r.options=e.widget.extend({},r.options),e.each(s,function(t,s){return e.isFunction(s)?(h[t]=function(){var e=function(){return i.prototype[t].apply(this,arguments)},n=function(e){return i.prototype[t].apply(this,e)};return function(){var t,i=this._super,a=this._superApply;return this._super=e,this._superApply=n,t=s.apply(this,arguments),this._super=i,this._superApply=a,t}}(),void 0):(h[t]=s,void 0)}),o.prototype=e.widget.extend(r,{widgetEventPrefix:a?r.widgetEventPrefix||t:t},h,{constructor:o,namespace:l,widgetName:t,widgetFullName:n}),a?(e.each(a._childConstructors,function(t,i){var s=i.prototype;e.widget(s.namespace+"."+s.widgetName,o,i._proto)}),delete a._childConstructors):i._childConstructors.push(o),e.widget.bridge(t,o),o},e.widget.extend=function(t){for(var i,s,n=a.call(arguments,1),o=0,r=n.length;r>o;o++)for(i in n[o])s=n[o][i],n[o].hasOwnProperty(i)&&void 0!==s&&(t[i]=e.isPlainObject(s)?e.isPlainObject(t[i])?e.widget.extend({},t[i],s):e.widget.extend({},s):s);return t},e.widget.bridge=function(t,i){var s=i.prototype.widgetFullName||t;e.fn[t]=function(n){var o="string"==typeof n,r=a.call(arguments,1),h=this;return o?this.each(function(){var i,a=e.data(this,s);return"instance"===n?(h=a,!1):a?e.isFunction(a[n])&&"_"!==n.charAt(0)?(i=a[n].apply(a,r),i!==a&&void 0!==i?(h=i&&i.jquery?h.pushStack(i.get()):i,!1):void 0):e.error("no such method '"+n+"' for "+t+" widget instance"):e.error("cannot call methods on "+t+" prior to initialization; "+"attempted to call method '"+n+"'")}):(r.length&&(n=e.widget.extend.apply(null,[n].concat(r))),this.each(function(){var t=e.data(this,s);t?(t.option(n||{}),t._init&&t._init()):e.data(this,s,new i(n,this))})),h}},e.Widget=function(){},e.Widget._childConstructors=[],e.Widget.prototype={widgetName:"widget",widgetEventPrefix:"",defaultElement:"<div>",options:{disabled:!1,create:null},_createWidget:function(t,i){i=e(i||this.defaultElement||this)[0],this.element=e(i),this.uuid=n++,this.eventNamespace="."+this.widgetName+this.uuid,this.bindings=e(),this.hoverable=e(),this.focusable=e(),i!==this&&(e.data(i,this.widgetFullName,this),this._on(!0,this.element,{remove:function(e){e.target===i&&this.destroy()}}),this.document=e(i.style?i.ownerDocument:i.document||i),this.window=e(this.document[0].defaultView||this.document[0].parentWindow)),this.options=e.widget.extend({},this.options,this._getCreateOptions(),t),this._create(),this._trigger("create",null,this._getCreateEventData()),this._init()},_getCreateOptions:e.noop,_getCreateEventData:e.noop,_create:e.noop,_init:e.noop,destroy:function(){this._destroy(),this.element.unbind(this.eventNamespace).removeData(this.widgetFullName).removeData(e.camelCase(this.widgetFullName)),this.widget().unbind(this.eventNamespace).removeAttr("aria-disabled").removeClass(this.widgetFullName+"-disabled "+"ui-state-disabled"),this.bindings.unbind(this.eventNamespace),this.hoverable.removeClass("ui-state-hover"),this.focusable.removeClass("ui-state-focus")},_destroy:e.noop,widget:function(){return this.element},option:function(t,i){var s,n,a,o=t;if(0===arguments.length)return e.widget.extend({},this.options);if("string"==typeof t)if(o={},s=t.split("."),t=s.shift(),s.length){for(n=o[t]=e.widget.extend({},this.options[t]),a=0;s.length-1>a;a++)n[s[a]]=n[s[a]]||{},n=n[s[a]];if(t=s.pop(),1===arguments.length)return void 0===n[t]?null:n[t];n[t]=i}else{if(1===arguments.length)return void 0===this.options[t]?null:this.options[t];o[t]=i}return this._setOptions(o),this},_setOptions:function(e){var t;for(t in e)this._setOption(t,e[t]);return this},_setOption:function(e,t){return this.options[e]=t,"disabled"===e&&(this.widget().toggleClass(this.widgetFullName+"-disabled",!!t),t&&(this.hoverable.removeClass("ui-state-hover"),this.focusable.removeClass("ui-state-focus"))),this},enable:function(){return this._setOptions({disabled:!1})},disable:function(){return this._setOptions({disabled:!0})},_on:function(t,i,s){var n,a=this;"boolean"!=typeof t&&(s=i,i=t,t=!1),s?(i=n=e(i),this.bindings=this.bindings.add(i)):(s=i,i=this.element,n=this.widget()),e.each(s,function(s,o){function r(){return t||a.options.disabled!==!0&&!e(this).hasClass("ui-state-disabled")?("string"==typeof o?a[o]:o).apply(a,arguments):void 0}"string"!=typeof o&&(r.guid=o.guid=o.guid||r.guid||e.guid++);var h=s.match(/^([\w:-]*)\s*(.*)$/),l=h[1]+a.eventNamespace,u=h[2];u?n.delegate(u,l,r):i.bind(l,r)})},_off:function(t,i){i=(i||"").split(" ").join(this.eventNamespace+" ")+this.eventNamespace,t.unbind(i).undelegate(i),this.bindings=e(this.bindings.not(t).get()),this.focusable=e(this.focusable.not(t).get()),this.hoverable=e(this.hoverable.not(t).get())},_delay:function(e,t){function i(){return("string"==typeof e?s[e]:e).apply(s,arguments)}var s=this;return setTimeout(i,t||0)},_hoverable:function(t){this.hoverable=this.hoverable.add(t),this._on(t,{mouseenter:function(t){e(t.currentTarget).addClass("ui-state-hover")},mouseleave:function(t){e(t.currentTarget).removeClass("ui-state-hover")}})},_focusable:function(t){this.focusable=this.focusable.add(t),this._on(t,{focusin:function(t){e(t.currentTarget).addClass("ui-state-focus")},focusout:function(t){e(t.currentTarget).removeClass("ui-state-focus")}})},_trigger:function(t,i,s){var n,a,o=this.options[t];if(s=s||{},i=e.Event(i),i.type=(t===this.widgetEventPrefix?t:this.widgetEventPrefix+t).toLowerCase(),i.target=this.element[0],a=i.originalEvent)for(n in a)n in i||(i[n]=a[n]);return this.element.trigger(i,s),!(e.isFunction(o)&&o.apply(this.element[0],[i].concat(s))===!1||i.isDefaultPrevented())}},e.each({show:"fadeIn",hide:"fadeOut"},function(t,i){e.Widget.prototype["_"+t]=function(s,n,a){"string"==typeof n&&(n={effect:n});var o,r=n?n===!0||"number"==typeof n?i:n.effect||i:t;n=n||{},"number"==typeof n&&(n={duration:n}),o=!e.isEmptyObject(n),n.complete=a,n.delay&&s.delay(n.delay),o&&e.effects&&e.effects.effect[r]?s[t](n):r!==t&&s[r]?s[r](n.duration,n.easing,a):s.queue(function(i){e(this)[t](),a&&a.call(s[0]),i()})}}),e.widget;var o=!1;e(document).mouseup(function(){o=!1}),e.widget("ui.mouse",{version:"1.11.4",options:{cancel:"input,textarea,button,select,option",distance:1,delay:0},_mouseInit:function(){var t=this;this.element.bind("mousedown."+this.widgetName,function(e){return t._mouseDown(e)}).bind("click."+this.widgetName,function(i){return!0===e.data(i.target,t.widgetName+".preventClickEvent")?(e.removeData(i.target,t.widgetName+".preventClickEvent"),i.stopImmediatePropagation(),!1):void 0}),this.started=!1},_mouseDestroy:function(){this.element.unbind("."+this.widgetName),this._mouseMoveDelegate&&this.document.unbind("mousemove."+this.widgetName,this._mouseMoveDelegate).unbind("mouseup."+this.widgetName,this._mouseUpDelegate)},_mouseDown:function(t){if(!o){this._mouseMoved=!1,this._mouseStarted&&this._mouseUp(t),this._mouseDownEvent=t;var i=this,s=1===t.which,n="string"==typeof this.options.cancel&&t.target.nodeName?e(t.target).closest(this.options.cancel).length:!1;return s&&!n&&this._mouseCapture(t)?(this.mouseDelayMet=!this.options.delay,this.mouseDelayMet||(this._mouseDelayTimer=setTimeout(function(){i.mouseDelayMet=!0},this.options.delay)),this._mouseDistanceMet(t)&&this._mouseDelayMet(t)&&(this._mouseStarted=this._mouseStart(t)!==!1,!this._mouseStarted)?(t.preventDefault(),!0):(!0===e.data(t.target,this.widgetName+".preventClickEvent")&&e.removeData(t.target,this.widgetName+".preventClickEvent"),this._mouseMoveDelegate=function(e){return i._mouseMove(e)},this._mouseUpDelegate=function(e){return i._mouseUp(e)},this.document.bind("mousemove."+this.widgetName,this._mouseMoveDelegate).bind("mouseup."+this.widgetName,this._mouseUpDelegate),t.preventDefault(),o=!0,!0)):!0}},_mouseMove:function(t){if(this._mouseMoved){if(e.ui.ie&&(!document.documentMode||9>document.documentMode)&&!t.button)return this._mouseUp(t);if(!t.which)return this._mouseUp(t)}return(t.which||t.button)&&(this._mouseMoved=!0),this._mouseStarted?(this._mouseDrag(t),t.preventDefault()):(this._mouseDistanceMet(t)&&this._mouseDelayMet(t)&&(this._mouseStarted=this._mouseStart(this._mouseDownEvent,t)!==!1,this._mouseStarted?this._mouseDrag(t):this._mouseUp(t)),!this._mouseStarted)},_mouseUp:function(t){return this.document.unbind("mousemove."+this.widgetName,this._mouseMoveDelegate).unbind("mouseup."+this.widgetName,this._mouseUpDelegate),this._mouseStarted&&(this._mouseStarted=!1,t.target===this._mouseDownEvent.target&&e.data(t.target,this.widgetName+".preventClickEvent",!0),this._mouseStop(t)),o=!1,!1},_mouseDistanceMet:function(e){return Math.max(Math.abs(this._mouseDownEvent.pageX-e.pageX),Math.abs(this._mouseDownEvent.pageY-e.pageY))>=this.options.distance},_mouseDelayMet:function(){return this.mouseDelayMet},_mouseStart:function(){},_mouseDrag:function(){},_mouseStop:function(){},_mouseCapture:function(){return!0}}),function(){function t(e,t,i){return[parseFloat(e[0])*(p.test(e[0])?t/100:1),parseFloat(e[1])*(p.test(e[1])?i/100:1)]}function i(t,i){return parseInt(e.css(t,i),10)||0}function s(t){var i=t[0];return 9===i.nodeType?{width:t.width(),height:t.height(),offset:{top:0,left:0}}:e.isWindow(i)?{width:t.width(),height:t.height(),offset:{top:t.scrollTop(),left:t.scrollLeft()}}:i.preventDefault?{width:0,height:0,offset:{top:i.pageY,left:i.pageX}}:{width:t.outerWidth(),height:t.outerHeight(),offset:t.offset()}}e.ui=e.ui||{};var n,a,o=Math.max,r=Math.abs,h=Math.round,l=/left|center|right/,u=/top|center|bottom/,d=/[\+\-]\d+(\.[\d]+)?%?/,c=/^\w+/,p=/%$/,f=e.fn.position;e.position={scrollbarWidth:function(){if(void 0!==n)return n;var t,i,s=e("<div style='display:block;position:absolute;width:50px;height:50px;overflow:hidden;'><div style='height:100px;width:auto;'></div></div>"),a=s.children()[0];return e("body").append(s),t=a.offsetWidth,s.css("overflow","scroll"),i=a.offsetWidth,t===i&&(i=s[0].clientWidth),s.remove(),n=t-i},getScrollInfo:function(t){var i=t.isWindow||t.isDocument?"":t.element.css("overflow-x"),s=t.isWindow||t.isDocument?"":t.element.css("overflow-y"),n="scroll"===i||"auto"===i&&t.width<t.element[0].scrollWidth,a="scroll"===s||"auto"===s&&t.height<t.element[0].scrollHeight;return{width:a?e.position.scrollbarWidth():0,height:n?e.position.scrollbarWidth():0}},getWithinInfo:function(t){var i=e(t||window),s=e.isWindow(i[0]),n=!!i[0]&&9===i[0].nodeType;return{element:i,isWindow:s,isDocument:n,offset:i.offset()||{left:0,top:0},scrollLeft:i.scrollLeft(),scrollTop:i.scrollTop(),width:s||n?i.width():i.outerWidth(),height:s||n?i.height():i.outerHeight()}}},e.fn.position=function(n){if(!n||!n.of)return f.apply(this,arguments);n=e.extend({},n);var p,m,g,v,y,b,_=e(n.of),x=e.position.getWithinInfo(n.within),w=e.position.getScrollInfo(x),k=(n.collision||"flip").split(" "),T={};return b=s(_),_[0].preventDefault&&(n.at="left top"),m=b.width,g=b.height,v=b.offset,y=e.extend({},v),e.each(["my","at"],function(){var e,t,i=(n[this]||"").split(" ");1===i.length&&(i=l.test(i[0])?i.concat(["center"]):u.test(i[0])?["center"].concat(i):["center","center"]),i[0]=l.test(i[0])?i[0]:"center",i[1]=u.test(i[1])?i[1]:"center",e=d.exec(i[0]),t=d.exec(i[1]),T[this]=[e?e[0]:0,t?t[0]:0],n[this]=[c.exec(i[0])[0],c.exec(i[1])[0]]}),1===k.length&&(k[1]=k[0]),"right"===n.at[0]?y.left+=m:"center"===n.at[0]&&(y.left+=m/2),"bottom"===n.at[1]?y.top+=g:"center"===n.at[1]&&(y.top+=g/2),p=t(T.at,m,g),y.left+=p[0],y.top+=p[1],this.each(function(){var s,l,u=e(this),d=u.outerWidth(),c=u.outerHeight(),f=i(this,"marginLeft"),b=i(this,"marginTop"),D=d+f+i(this,"marginRight")+w.width,S=c+b+i(this,"marginBottom")+w.height,N=e.extend({},y),M=t(T.my,u.outerWidth(),u.outerHeight());"right"===n.my[0]?N.left-=d:"center"===n.my[0]&&(N.left-=d/2),"bottom"===n.my[1]?N.top-=c:"center"===n.my[1]&&(N.top-=c/2),N.left+=M[0],N.top+=M[1],a||(N.left=h(N.left),N.top=h(N.top)),s={marginLeft:f,marginTop:b},e.each(["left","top"],function(t,i){e.ui.position[k[t]]&&e.ui.position[k[t]][i](N,{targetWidth:m,targetHeight:g,elemWidth:d,elemHeight:c,collisionPosition:s,collisionWidth:D,collisionHeight:S,offset:[p[0]+M[0],p[1]+M[1]],my:n.my,at:n.at,within:x,elem:u})}),n.using&&(l=function(e){var t=v.left-N.left,i=t+m-d,s=v.top-N.top,a=s+g-c,h={target:{element:_,left:v.left,top:v.top,width:m,height:g},element:{element:u,left:N.left,top:N.top,width:d,height:c},horizontal:0>i?"left":t>0?"right":"center",vertical:0>a?"top":s>0?"bottom":"middle"};d>m&&m>r(t+i)&&(h.horizontal="center"),c>g&&g>r(s+a)&&(h.vertical="middle"),h.important=o(r(t),r(i))>o(r(s),r(a))?"horizontal":"vertical",n.using.call(this,e,h)}),u.offset(e.extend(N,{using:l}))})},e.ui.position={fit:{left:function(e,t){var i,s=t.within,n=s.isWindow?s.scrollLeft:s.offset.left,a=s.width,r=e.left-t.collisionPosition.marginLeft,h=n-r,l=r+t.collisionWidth-a-n;t.collisionWidth>a?h>0&&0>=l?(i=e.left+h+t.collisionWidth-a-n,e.left+=h-i):e.left=l>0&&0>=h?n:h>l?n+a-t.collisionWidth:n:h>0?e.left+=h:l>0?e.left-=l:e.left=o(e.left-r,e.left)},top:function(e,t){var i,s=t.within,n=s.isWindow?s.scrollTop:s.offset.top,a=t.within.height,r=e.top-t.collisionPosition.marginTop,h=n-r,l=r+t.collisionHeight-a-n;t.collisionHeight>a?h>0&&0>=l?(i=e.top+h+t.collisionHeight-a-n,e.top+=h-i):e.top=l>0&&0>=h?n:h>l?n+a-t.collisionHeight:n:h>0?e.top+=h:l>0?e.top-=l:e.top=o(e.top-r,e.top)}},flip:{left:function(e,t){var i,s,n=t.within,a=n.offset.left+n.scrollLeft,o=n.width,h=n.isWindow?n.scrollLeft:n.offset.left,l=e.left-t.collisionPosition.marginLeft,u=l-h,d=l+t.collisionWidth-o-h,c="left"===t.my[0]?-t.elemWidth:"right"===t.my[0]?t.elemWidth:0,p="left"===t.at[0]?t.targetWidth:"right"===t.at[0]?-t.targetWidth:0,f=-2*t.offset[0];0>u?(i=e.left+c+p+f+t.collisionWidth-o-a,(0>i||r(u)>i)&&(e.left+=c+p+f)):d>0&&(s=e.left-t.collisionPosition.marginLeft+c+p+f-h,(s>0||d>r(s))&&(e.left+=c+p+f))},top:function(e,t){var i,s,n=t.within,a=n.offset.top+n.scrollTop,o=n.height,h=n.isWindow?n.scrollTop:n.offset.top,l=e.top-t.collisionPosition.marginTop,u=l-h,d=l+t.collisionHeight-o-h,c="top"===t.my[1],p=c?-t.elemHeight:"bottom"===t.my[1]?t.elemHeight:0,f="top"===t.at[1]?t.targetHeight:"bottom"===t.at[1]?-t.targetHeight:0,m=-2*t.offset[1];0>u?(s=e.top+p+f+m+t.collisionHeight-o-a,(0>s||r(u)>s)&&(e.top+=p+f+m)):d>0&&(i=e.top-t.collisionPosition.marginTop+p+f+m-h,(i>0||d>r(i))&&(e.top+=p+f+m))}},flipfit:{left:function(){e.ui.position.flip.left.apply(this,arguments),e.ui.position.fit.left.apply(this,arguments)},top:function(){e.ui.position.flip.top.apply(this,arguments),e.ui.position.fit.top.apply(this,arguments)}}},function(){var t,i,s,n,o,r=document.getElementsByTagName("body")[0],h=document.createElement("div");t=document.createElement(r?"div":"body"),s={visibility:"hidden",width:0,height:0,border:0,margin:0,background:"none"},r&&e.extend(s,{position:"absolute",left:"-1000px",top:"-1000px"});for(o in s)t.style[o]=s[o];t.appendChild(h),i=r||document.documentElement,i.insertBefore(t,i.firstChild),h.style.cssText="position: absolute; left: 10.7432222px;",n=e(h).offset().left,a=n>10&&11>n,t.innerHTML="",i.removeChild(t)}()}(),e.ui.position,e.widget("ui.draggable",e.ui.mouse,{version:"1.11.4",widgetEventPrefix:"drag",options:{addClasses:!0,appendTo:"parent",axis:!1,connectToSortable:!1,containment:!1,cursor:"auto",cursorAt:!1,grid:!1,handle:!1,helper:"original",iframeFix:!1,opacity:!1,refreshPositions:!1,revert:!1,revertDuration:500,scope:"default",scroll:!0,scrollSensitivity:20,scrollSpeed:20,snap:!1,snapMode:"both",snapTolerance:20,stack:!1,zIndex:!1,drag:null,start:null,stop:null},_create:function(){"original"===this.options.helper&&this._setPositionRelative(),this.options.addClasses&&this.element.addClass("ui-draggable"),this.options.disabled&&this.element.addClass("ui-draggable-disabled"),this._setHandleClassName(),this._mouseInit()},_setOption:function(e,t){this._super(e,t),"handle"===e&&(this._removeHandleClassName(),this._setHandleClassName())},_destroy:function(){return(this.helper||this.element).is(".ui-draggable-dragging")?(this.destroyOnClear=!0,void 0):(this.element.removeClass("ui-draggable ui-draggable-dragging ui-draggable-disabled"),this._removeHandleClassName(),this._mouseDestroy(),void 0)},_mouseCapture:function(t){var i=this.options;return this._blurActiveElement(t),this.helper||i.disabled||e(t.target).closest(".ui-resizable-handle").length>0?!1:(this.handle=this._getHandle(t),this.handle?(this._blockFrames(i.iframeFix===!0?"iframe":i.iframeFix),!0):!1)},_blockFrames:function(t){this.iframeBlocks=this.document.find(t).map(function(){var t=e(this);return e("<div>").css("position","absolute").appendTo(t.parent()).outerWidth(t.outerWidth()).outerHeight(t.outerHeight()).offset(t.offset())[0]})},_unblockFrames:function(){this.iframeBlocks&&(this.iframeBlocks.remove(),delete this.iframeBlocks)},_blurActiveElement:function(t){var i=this.document[0];if(this.handleElement.is(t.target))try{i.activeElement&&"body"!==i.activeElement.nodeName.toLowerCase()&&e(i.activeElement).blur()}catch(s){}},_mouseStart:function(t){var i=this.options;return this.helper=this._createHelper(t),this.helper.addClass("ui-draggable-dragging"),this._cacheHelperProportions(),e.ui.ddmanager&&(e.ui.ddmanager.current=this),this._cacheMargins(),this.cssPosition=this.helper.css("position"),this.scrollParent=this.helper.scrollParent(!0),this.offsetParent=this.helper.offsetParent(),this.hasFixedAncestor=this.helper.parents().filter(function(){return"fixed"===e(this).css("position")}).length>0,this.positionAbs=this.element.offset(),this._refreshOffsets(t),this.originalPosition=this.position=this._generatePosition(t,!1),this.originalPageX=t.pageX,this.originalPageY=t.pageY,i.cursorAt&&this._adjustOffsetFromHelper(i.cursorAt),this._setContainment(),this._trigger("start",t)===!1?(this._clear(),!1):(this._cacheHelperProportions(),e.ui.ddmanager&&!i.dropBehaviour&&e.ui.ddmanager.prepareOffsets(this,t),this._normalizeRightBottom(),this._mouseDrag(t,!0),e.ui.ddmanager&&e.ui.ddmanager.dragStart(this,t),!0)},_refreshOffsets:function(e){this.offset={top:this.positionAbs.top-this.margins.top,left:this.positionAbs.left-this.margins.left,scroll:!1,parent:this._getParentOffset(),relative:this._getRelativeOffset()},this.offset.click={left:e.pageX-this.offset.left,top:e.pageY-this.offset.top}},_mouseDrag:function(t,i){if(this.hasFixedAncestor&&(this.offset.parent=this._getParentOffset()),this.position=this._generatePosition(t,!0),this.positionAbs=this._convertPositionTo("absolute"),!i){var s=this._uiHash();if(this._trigger("drag",t,s)===!1)return this._mouseUp({}),!1;this.position=s.position}return this.helper[0].style.left=this.position.left+"px",this.helper[0].style.top=this.position.top+"px",e.ui.ddmanager&&e.ui.ddmanager.drag(this,t),!1},_mouseStop:function(t){var i=this,s=!1;return e.ui.ddmanager&&!this.options.dropBehaviour&&(s=e.ui.ddmanager.drop(this,t)),this.dropped&&(s=this.dropped,this.dropped=!1),"invalid"===this.options.revert&&!s||"valid"===this.options.revert&&s||this.options.revert===!0||e.isFunction(this.options.revert)&&this.options.revert.call(this.element,s)?e(this.helper).animate(this.originalPosition,parseInt(this.options.revertDuration,10),function(){i._trigger("stop",t)!==!1&&i._clear()}):this._trigger("stop",t)!==!1&&this._clear(),!1},_mouseUp:function(t){return this._unblockFrames(),e.ui.ddmanager&&e.ui.ddmanager.dragStop(this,t),this.handleElement.is(t.target)&&this.element.focus(),e.ui.mouse.prototype._mouseUp.call(this,t)},cancel:function(){return this.helper.is(".ui-draggable-dragging")?this._mouseUp({}):this._clear(),this},_getHandle:function(t){return this.options.handle?!!e(t.target).closest(this.element.find(this.options.handle)).length:!0},_setHandleClassName:function(){this.handleElement=this.options.handle?this.element.find(this.options.handle):this.element,this.handleElement.addClass("ui-draggable-handle")},_removeHandleClassName:function(){this.handleElement.removeClass("ui-draggable-handle")},_createHelper:function(t){var i=this.options,s=e.isFunction(i.helper),n=s?e(i.helper.apply(this.element[0],[t])):"clone"===i.helper?this.element.clone().removeAttr("id"):this.element;return n.parents("body").length||n.appendTo("parent"===i.appendTo?this.element[0].parentNode:i.appendTo),s&&n[0]===this.element[0]&&this._setPositionRelative(),n[0]===this.element[0]||/(fixed|absolute)/.test(n.css("position"))||n.css("position","absolute"),n},_setPositionRelative:function(){/^(?:r|a|f)/.test(this.element.css("position"))||(this.element[0].style.position="relative")},_adjustOffsetFromHelper:function(t){"string"==typeof t&&(t=t.split(" ")),e.isArray(t)&&(t={left:+t[0],top:+t[1]||0}),"left"in t&&(this.offset.click.left=t.left+this.margins.left),"right"in t&&(this.offset.click.left=this.helperProportions.width-t.right+this.margins.left),"top"in t&&(this.offset.click.top=t.top+this.margins.top),"bottom"in t&&(this.offset.click.top=this.helperProportions.height-t.bottom+this.margins.top)},_isRootNode:function(e){return/(html|body)/i.test(e.tagName)||e===this.document[0]},_getParentOffset:function(){var t=this.offsetParent.offset(),i=this.document[0];return"absolute"===this.cssPosition&&this.scrollParent[0]!==i&&e.contains(this.scrollParent[0],this.offsetParent[0])&&(t.left+=this.scrollParent.scrollLeft(),t.top+=this.scrollParent.scrollTop()),this._isRootNode(this.offsetParent[0])&&(t={top:0,left:0}),{top:t.top+(parseInt(this.offsetParent.css("borderTopWidth"),10)||0),left:t.left+(parseInt(this.offsetParent.css("borderLeftWidth"),10)||0)}},_getRelativeOffset:function(){if("relative"!==this.cssPosition)return{top:0,left:0};var e=this.element.position(),t=this._isRootNode(this.scrollParent[0]);return{top:e.top-(parseInt(this.helper.css("top"),10)||0)+(t?0:this.scrollParent.scrollTop()),left:e.left-(parseInt(this.helper.css("left"),10)||0)+(t?0:this.scrollParent.scrollLeft())}},_cacheMargins:function(){this.margins={left:parseInt(this.element.css("marginLeft"),10)||0,top:parseInt(this.element.css("marginTop"),10)||0,right:parseInt(this.element.css("marginRight"),10)||0,bottom:parseInt(this.element.css("marginBottom"),10)||0}},_cacheHelperProportions:function(){this.helperProportions={width:this.helper.outerWidth(),height:this.helper.outerHeight()}},_setContainment:function(){var t,i,s,n=this.options,a=this.document[0];return this.relativeContainer=null,n.containment?"window"===n.containment?(this.containment=[e(window).scrollLeft()-this.offset.relative.left-this.offset.parent.left,e(window).scrollTop()-this.offset.relative.top-this.offset.parent.top,e(window).scrollLeft()+e(window).width()-this.helperProportions.width-this.margins.left,e(window).scrollTop()+(e(window).height()||a.body.parentNode.scrollHeight)-this.helperProportions.height-this.margins.top],void 0):"document"===n.containment?(this.containment=[0,0,e(a).width()-this.helperProportions.width-this.margins.left,(e(a).height()||a.body.parentNode.scrollHeight)-this.helperProportions.height-this.margins.top],void 0):n.containment.constructor===Array?(this.containment=n.containment,void 0):("parent"===n.containment&&(n.containment=this.helper[0].parentNode),i=e(n.containment),s=i[0],s&&(t=/(scroll|auto)/.test(i.css("overflow")),this.containment=[(parseInt(i.css("borderLeftWidth"),10)||0)+(parseInt(i.css("paddingLeft"),10)||0),(parseInt(i.css("borderTopWidth"),10)||0)+(parseInt(i.css("paddingTop"),10)||0),(t?Math.max(s.scrollWidth,s.offsetWidth):s.offsetWidth)-(parseInt(i.css("borderRightWidth"),10)||0)-(parseInt(i.css("paddingRight"),10)||0)-this.helperProportions.width-this.margins.left-this.margins.right,(t?Math.max(s.scrollHeight,s.offsetHeight):s.offsetHeight)-(parseInt(i.css("borderBottomWidth"),10)||0)-(parseInt(i.css("paddingBottom"),10)||0)-this.helperProportions.height-this.margins.top-this.margins.bottom],this.relativeContainer=i),void 0):(this.containment=null,void 0)},_convertPositionTo:function(e,t){t||(t=this.position);var i="absolute"===e?1:-1,s=this._isRootNode(this.scrollParent[0]);return{top:t.top+this.offset.relative.top*i+this.offset.parent.top*i-("fixed"===this.cssPosition?-this.offset.scroll.top:s?0:this.offset.scroll.top)*i,left:t.left+this.offset.relative.left*i+this.offset.parent.left*i-("fixed"===this.cssPosition?-this.offset.scroll.left:s?0:this.offset.scroll.left)*i}},_generatePosition:function(e,t){var i,s,n,a,o=this.options,r=this._isRootNode(this.scrollParent[0]),h=e.pageX,l=e.pageY;return r&&this.offset.scroll||(this.offset.scroll={top:this.scrollParent.scrollTop(),left:this.scrollParent.scrollLeft()}),t&&(this.containment&&(this.relativeContainer?(s=this.relativeContainer.offset(),i=[this.containment[0]+s.left,this.containment[1]+s.top,this.containment[2]+s.left,this.containment[3]+s.top]):i=this.containment,e.pageX-this.offset.click.left<i[0]&&(h=i[0]+this.offset.click.left),e.pageY-this.offset.click.top<i[1]&&(l=i[1]+this.offset.click.top),e.pageX-this.offset.click.left>i[2]&&(h=i[2]+this.offset.click.left),e.pageY-this.offset.click.top>i[3]&&(l=i[3]+this.offset.click.top)),o.grid&&(n=o.grid[1]?this.originalPageY+Math.round((l-this.originalPageY)/o.grid[1])*o.grid[1]:this.originalPageY,l=i?n-this.offset.click.top>=i[1]||n-this.offset.click.top>i[3]?n:n-this.offset.click.top>=i[1]?n-o.grid[1]:n+o.grid[1]:n,a=o.grid[0]?this.originalPageX+Math.round((h-this.originalPageX)/o.grid[0])*o.grid[0]:this.originalPageX,h=i?a-this.offset.click.left>=i[0]||a-this.offset.click.left>i[2]?a:a-this.offset.click.left>=i[0]?a-o.grid[0]:a+o.grid[0]:a),"y"===o.axis&&(h=this.originalPageX),"x"===o.axis&&(l=this.originalPageY)),{top:l-this.offset.click.top-this.offset.relative.top-this.offset.parent.top+("fixed"===this.cssPosition?-this.offset.scroll.top:r?0:this.offset.scroll.top),left:h-this.offset.click.left-this.offset.relative.left-this.offset.parent.left+("fixed"===this.cssPosition?-this.offset.scroll.left:r?0:this.offset.scroll.left)}},_clear:function(){this.helper.removeClass("ui-draggable-dragging"),this.helper[0]===this.element[0]||this.cancelHelperRemoval||this.helper.remove(),this.helper=null,this.cancelHelperRemoval=!1,this.destroyOnClear&&this.destroy()},_normalizeRightBottom:function(){"y"!==this.options.axis&&"auto"!==this.helper.css("right")&&(this.helper.width(this.helper.width()),this.helper.css("right","auto")),"x"!==this.options.axis&&"auto"!==this.helper.css("bottom")&&(this.helper.height(this.helper.height()),this.helper.css("bottom","auto"))},_trigger:function(t,i,s){return s=s||this._uiHash(),e.ui.plugin.call(this,t,[i,s,this],!0),/^(drag|start|stop)/.test(t)&&(this.positionAbs=this._convertPositionTo("absolute"),s.offset=this.positionAbs),e.Widget.prototype._trigger.call(this,t,i,s)},plugins:{},_uiHash:function(){return{helper:this.helper,position:this.position,originalPosition:this.originalPosition,offset:this.positionAbs}}}),e.ui.plugin.add("draggable","connectToSortable",{start:function(t,i,s){var n=e.extend({},i,{item:s.element});s.sortables=[],e(s.options.connectToSortable).each(function(){var i=e(this).sortable("instance");i&&!i.options.disabled&&(s.sortables.push(i),i.refreshPositions(),i._trigger("activate",t,n))})},stop:function(t,i,s){var n=e.extend({},i,{item:s.element});s.cancelHelperRemoval=!1,e.each(s.sortables,function(){var e=this;e.isOver?(e.isOver=0,s.cancelHelperRemoval=!0,e.cancelHelperRemoval=!1,e._storedCSS={position:e.placeholder.css("position"),top:e.placeholder.css("top"),left:e.placeholder.css("left")},e._mouseStop(t),e.options.helper=e.options._helper):(e.cancelHelperRemoval=!0,e._trigger("deactivate",t,n))})},drag:function(t,i,s){e.each(s.sortables,function(){var n=!1,a=this;a.positionAbs=s.positionAbs,a.helperProportions=s.helperProportions,a.offset.click=s.offset.click,a._intersectsWith(a.containerCache)&&(n=!0,e.each(s.sortables,function(){return this.positionAbs=s.positionAbs,this.helperProportions=s.helperProportions,this.offset.click=s.offset.click,this!==a&&this._intersectsWith(this.containerCache)&&e.contains(a.element[0],this.element[0])&&(n=!1),n
})),n?(a.isOver||(a.isOver=1,s._parent=i.helper.parent(),a.currentItem=i.helper.appendTo(a.element).data("ui-sortable-item",!0),a.options._helper=a.options.helper,a.options.helper=function(){return i.helper[0]},t.target=a.currentItem[0],a._mouseCapture(t,!0),a._mouseStart(t,!0,!0),a.offset.click.top=s.offset.click.top,a.offset.click.left=s.offset.click.left,a.offset.parent.left-=s.offset.parent.left-a.offset.parent.left,a.offset.parent.top-=s.offset.parent.top-a.offset.parent.top,s._trigger("toSortable",t),s.dropped=a.element,e.each(s.sortables,function(){this.refreshPositions()}),s.currentItem=s.element,a.fromOutside=s),a.currentItem&&(a._mouseDrag(t),i.position=a.position)):a.isOver&&(a.isOver=0,a.cancelHelperRemoval=!0,a.options._revert=a.options.revert,a.options.revert=!1,a._trigger("out",t,a._uiHash(a)),a._mouseStop(t,!0),a.options.revert=a.options._revert,a.options.helper=a.options._helper,a.placeholder&&a.placeholder.remove(),i.helper.appendTo(s._parent),s._refreshOffsets(t),i.position=s._generatePosition(t,!0),s._trigger("fromSortable",t),s.dropped=!1,e.each(s.sortables,function(){this.refreshPositions()}))})}}),e.ui.plugin.add("draggable","cursor",{start:function(t,i,s){var n=e("body"),a=s.options;n.css("cursor")&&(a._cursor=n.css("cursor")),n.css("cursor",a.cursor)},stop:function(t,i,s){var n=s.options;n._cursor&&e("body").css("cursor",n._cursor)}}),e.ui.plugin.add("draggable","opacity",{start:function(t,i,s){var n=e(i.helper),a=s.options;n.css("opacity")&&(a._opacity=n.css("opacity")),n.css("opacity",a.opacity)},stop:function(t,i,s){var n=s.options;n._opacity&&e(i.helper).css("opacity",n._opacity)}}),e.ui.plugin.add("draggable","scroll",{start:function(e,t,i){i.scrollParentNotHidden||(i.scrollParentNotHidden=i.helper.scrollParent(!1)),i.scrollParentNotHidden[0]!==i.document[0]&&"HTML"!==i.scrollParentNotHidden[0].tagName&&(i.overflowOffset=i.scrollParentNotHidden.offset())},drag:function(t,i,s){var n=s.options,a=!1,o=s.scrollParentNotHidden[0],r=s.document[0];o!==r&&"HTML"!==o.tagName?(n.axis&&"x"===n.axis||(s.overflowOffset.top+o.offsetHeight-t.pageY<n.scrollSensitivity?o.scrollTop=a=o.scrollTop+n.scrollSpeed:t.pageY-s.overflowOffset.top<n.scrollSensitivity&&(o.scrollTop=a=o.scrollTop-n.scrollSpeed)),n.axis&&"y"===n.axis||(s.overflowOffset.left+o.offsetWidth-t.pageX<n.scrollSensitivity?o.scrollLeft=a=o.scrollLeft+n.scrollSpeed:t.pageX-s.overflowOffset.left<n.scrollSensitivity&&(o.scrollLeft=a=o.scrollLeft-n.scrollSpeed))):(n.axis&&"x"===n.axis||(t.pageY-e(r).scrollTop()<n.scrollSensitivity?a=e(r).scrollTop(e(r).scrollTop()-n.scrollSpeed):e(window).height()-(t.pageY-e(r).scrollTop())<n.scrollSensitivity&&(a=e(r).scrollTop(e(r).scrollTop()+n.scrollSpeed))),n.axis&&"y"===n.axis||(t.pageX-e(r).scrollLeft()<n.scrollSensitivity?a=e(r).scrollLeft(e(r).scrollLeft()-n.scrollSpeed):e(window).width()-(t.pageX-e(r).scrollLeft())<n.scrollSensitivity&&(a=e(r).scrollLeft(e(r).scrollLeft()+n.scrollSpeed)))),a!==!1&&e.ui.ddmanager&&!n.dropBehaviour&&e.ui.ddmanager.prepareOffsets(s,t)}}),e.ui.plugin.add("draggable","snap",{start:function(t,i,s){var n=s.options;s.snapElements=[],e(n.snap.constructor!==String?n.snap.items||":data(ui-draggable)":n.snap).each(function(){var t=e(this),i=t.offset();this!==s.element[0]&&s.snapElements.push({item:this,width:t.outerWidth(),height:t.outerHeight(),top:i.top,left:i.left})})},drag:function(t,i,s){var n,a,o,r,h,l,u,d,c,p,f=s.options,m=f.snapTolerance,g=i.offset.left,v=g+s.helperProportions.width,y=i.offset.top,b=y+s.helperProportions.height;for(c=s.snapElements.length-1;c>=0;c--)h=s.snapElements[c].left-s.margins.left,l=h+s.snapElements[c].width,u=s.snapElements[c].top-s.margins.top,d=u+s.snapElements[c].height,h-m>v||g>l+m||u-m>b||y>d+m||!e.contains(s.snapElements[c].item.ownerDocument,s.snapElements[c].item)?(s.snapElements[c].snapping&&s.options.snap.release&&s.options.snap.release.call(s.element,t,e.extend(s._uiHash(),{snapItem:s.snapElements[c].item})),s.snapElements[c].snapping=!1):("inner"!==f.snapMode&&(n=m>=Math.abs(u-b),a=m>=Math.abs(d-y),o=m>=Math.abs(h-v),r=m>=Math.abs(l-g),n&&(i.position.top=s._convertPositionTo("relative",{top:u-s.helperProportions.height,left:0}).top),a&&(i.position.top=s._convertPositionTo("relative",{top:d,left:0}).top),o&&(i.position.left=s._convertPositionTo("relative",{top:0,left:h-s.helperProportions.width}).left),r&&(i.position.left=s._convertPositionTo("relative",{top:0,left:l}).left)),p=n||a||o||r,"outer"!==f.snapMode&&(n=m>=Math.abs(u-y),a=m>=Math.abs(d-b),o=m>=Math.abs(h-g),r=m>=Math.abs(l-v),n&&(i.position.top=s._convertPositionTo("relative",{top:u,left:0}).top),a&&(i.position.top=s._convertPositionTo("relative",{top:d-s.helperProportions.height,left:0}).top),o&&(i.position.left=s._convertPositionTo("relative",{top:0,left:h}).left),r&&(i.position.left=s._convertPositionTo("relative",{top:0,left:l-s.helperProportions.width}).left)),!s.snapElements[c].snapping&&(n||a||o||r||p)&&s.options.snap.snap&&s.options.snap.snap.call(s.element,t,e.extend(s._uiHash(),{snapItem:s.snapElements[c].item})),s.snapElements[c].snapping=n||a||o||r||p)}}),e.ui.plugin.add("draggable","stack",{start:function(t,i,s){var n,a=s.options,o=e.makeArray(e(a.stack)).sort(function(t,i){return(parseInt(e(t).css("zIndex"),10)||0)-(parseInt(e(i).css("zIndex"),10)||0)});o.length&&(n=parseInt(e(o[0]).css("zIndex"),10)||0,e(o).each(function(t){e(this).css("zIndex",n+t)}),this.css("zIndex",n+o.length))}}),e.ui.plugin.add("draggable","zIndex",{start:function(t,i,s){var n=e(i.helper),a=s.options;n.css("zIndex")&&(a._zIndex=n.css("zIndex")),n.css("zIndex",a.zIndex)},stop:function(t,i,s){var n=s.options;n._zIndex&&e(i.helper).css("zIndex",n._zIndex)}}),e.ui.draggable,e.widget("ui.droppable",{version:"1.11.4",widgetEventPrefix:"drop",options:{accept:"*",activeClass:!1,addClasses:!0,greedy:!1,hoverClass:!1,scope:"default",tolerance:"intersect",activate:null,deactivate:null,drop:null,out:null,over:null},_create:function(){var t,i=this.options,s=i.accept;this.isover=!1,this.isout=!0,this.accept=e.isFunction(s)?s:function(e){return e.is(s)},this.proportions=function(){return arguments.length?(t=arguments[0],void 0):t?t:t={width:this.element[0].offsetWidth,height:this.element[0].offsetHeight}},this._addToManager(i.scope),i.addClasses&&this.element.addClass("ui-droppable")},_addToManager:function(t){e.ui.ddmanager.droppables[t]=e.ui.ddmanager.droppables[t]||[],e.ui.ddmanager.droppables[t].push(this)},_splice:function(e){for(var t=0;e.length>t;t++)e[t]===this&&e.splice(t,1)},_destroy:function(){var t=e.ui.ddmanager.droppables[this.options.scope];this._splice(t),this.element.removeClass("ui-droppable ui-droppable-disabled")},_setOption:function(t,i){if("accept"===t)this.accept=e.isFunction(i)?i:function(e){return e.is(i)};else if("scope"===t){var s=e.ui.ddmanager.droppables[this.options.scope];this._splice(s),this._addToManager(i)}this._super(t,i)},_activate:function(t){var i=e.ui.ddmanager.current;this.options.activeClass&&this.element.addClass(this.options.activeClass),i&&this._trigger("activate",t,this.ui(i))},_deactivate:function(t){var i=e.ui.ddmanager.current;this.options.activeClass&&this.element.removeClass(this.options.activeClass),i&&this._trigger("deactivate",t,this.ui(i))},_over:function(t){var i=e.ui.ddmanager.current;i&&(i.currentItem||i.element)[0]!==this.element[0]&&this.accept.call(this.element[0],i.currentItem||i.element)&&(this.options.hoverClass&&this.element.addClass(this.options.hoverClass),this._trigger("over",t,this.ui(i)))},_out:function(t){var i=e.ui.ddmanager.current;i&&(i.currentItem||i.element)[0]!==this.element[0]&&this.accept.call(this.element[0],i.currentItem||i.element)&&(this.options.hoverClass&&this.element.removeClass(this.options.hoverClass),this._trigger("out",t,this.ui(i)))},_drop:function(t,i){var s=i||e.ui.ddmanager.current,n=!1;return s&&(s.currentItem||s.element)[0]!==this.element[0]?(this.element.find(":data(ui-droppable)").not(".ui-draggable-dragging").each(function(){var i=e(this).droppable("instance");return i.options.greedy&&!i.options.disabled&&i.options.scope===s.options.scope&&i.accept.call(i.element[0],s.currentItem||s.element)&&e.ui.intersect(s,e.extend(i,{offset:i.element.offset()}),i.options.tolerance,t)?(n=!0,!1):void 0}),n?!1:this.accept.call(this.element[0],s.currentItem||s.element)?(this.options.activeClass&&this.element.removeClass(this.options.activeClass),this.options.hoverClass&&this.element.removeClass(this.options.hoverClass),this._trigger("drop",t,this.ui(s)),this.element):!1):!1},ui:function(e){return{draggable:e.currentItem||e.element,helper:e.helper,position:e.position,offset:e.positionAbs}}}),e.ui.intersect=function(){function e(e,t,i){return e>=t&&t+i>e}return function(t,i,s,n){if(!i.offset)return!1;var a=(t.positionAbs||t.position.absolute).left+t.margins.left,o=(t.positionAbs||t.position.absolute).top+t.margins.top,r=a+t.helperProportions.width,h=o+t.helperProportions.height,l=i.offset.left,u=i.offset.top,d=l+i.proportions().width,c=u+i.proportions().height;switch(s){case"fit":return a>=l&&d>=r&&o>=u&&c>=h;case"intersect":return a+t.helperProportions.width/2>l&&d>r-t.helperProportions.width/2&&o+t.helperProportions.height/2>u&&c>h-t.helperProportions.height/2;case"pointer":return e(n.pageY,u,i.proportions().height)&&e(n.pageX,l,i.proportions().width);case"touch":return(o>=u&&c>=o||h>=u&&c>=h||u>o&&h>c)&&(a>=l&&d>=a||r>=l&&d>=r||l>a&&r>d);default:return!1}}}(),e.ui.ddmanager={current:null,droppables:{"default":[]},prepareOffsets:function(t,i){var s,n,a=e.ui.ddmanager.droppables[t.options.scope]||[],o=i?i.type:null,r=(t.currentItem||t.element).find(":data(ui-droppable)").addBack();e:for(s=0;a.length>s;s++)if(!(a[s].options.disabled||t&&!a[s].accept.call(a[s].element[0],t.currentItem||t.element))){for(n=0;r.length>n;n++)if(r[n]===a[s].element[0]){a[s].proportions().height=0;continue e}a[s].visible="none"!==a[s].element.css("display"),a[s].visible&&("mousedown"===o&&a[s]._activate.call(a[s],i),a[s].offset=a[s].element.offset(),a[s].proportions({width:a[s].element[0].offsetWidth,height:a[s].element[0].offsetHeight}))}},drop:function(t,i){var s=!1;return e.each((e.ui.ddmanager.droppables[t.options.scope]||[]).slice(),function(){this.options&&(!this.options.disabled&&this.visible&&e.ui.intersect(t,this,this.options.tolerance,i)&&(s=this._drop.call(this,i)||s),!this.options.disabled&&this.visible&&this.accept.call(this.element[0],t.currentItem||t.element)&&(this.isout=!0,this.isover=!1,this._deactivate.call(this,i)))}),s},dragStart:function(t,i){t.element.parentsUntil("body").bind("scroll.droppable",function(){t.options.refreshPositions||e.ui.ddmanager.prepareOffsets(t,i)})},drag:function(t,i){t.options.refreshPositions&&e.ui.ddmanager.prepareOffsets(t,i),e.each(e.ui.ddmanager.droppables[t.options.scope]||[],function(){if(!this.options.disabled&&!this.greedyChild&&this.visible){var s,n,a,o=e.ui.intersect(t,this,this.options.tolerance,i),r=!o&&this.isover?"isout":o&&!this.isover?"isover":null;r&&(this.options.greedy&&(n=this.options.scope,a=this.element.parents(":data(ui-droppable)").filter(function(){return e(this).droppable("instance").options.scope===n}),a.length&&(s=e(a[0]).droppable("instance"),s.greedyChild="isover"===r)),s&&"isover"===r&&(s.isover=!1,s.isout=!0,s._out.call(s,i)),this[r]=!0,this["isout"===r?"isover":"isout"]=!1,this["isover"===r?"_over":"_out"].call(this,i),s&&"isout"===r&&(s.isout=!1,s.isover=!0,s._over.call(s,i)))}})},dragStop:function(t,i){t.element.parentsUntil("body").unbind("scroll.droppable"),t.options.refreshPositions||e.ui.ddmanager.prepareOffsets(t,i)}},e.ui.droppable,e.widget("ui.resizable",e.ui.mouse,{version:"1.11.4",widgetEventPrefix:"resize",options:{alsoResize:!1,animate:!1,animateDuration:"slow",animateEasing:"swing",aspectRatio:!1,autoHide:!1,containment:!1,ghost:!1,grid:!1,handles:"e,s,se",helper:!1,maxHeight:null,maxWidth:null,minHeight:10,minWidth:10,zIndex:90,resize:null,start:null,stop:null},_num:function(e){return parseInt(e,10)||0},_isNumber:function(e){return!isNaN(parseInt(e,10))},_hasScroll:function(t,i){if("hidden"===e(t).css("overflow"))return!1;var s=i&&"left"===i?"scrollLeft":"scrollTop",n=!1;return t[s]>0?!0:(t[s]=1,n=t[s]>0,t[s]=0,n)},_create:function(){var t,i,s,n,a,o=this,r=this.options;if(this.element.addClass("ui-resizable"),e.extend(this,{_aspectRatio:!!r.aspectRatio,aspectRatio:r.aspectRatio,originalElement:this.element,_proportionallyResizeElements:[],_helper:r.helper||r.ghost||r.animate?r.helper||"ui-resizable-helper":null}),this.element[0].nodeName.match(/^(canvas|textarea|input|select|button|img)$/i)&&(this.element.wrap(e("<div class='ui-wrapper' style='overflow: hidden;'></div>").css({position:this.element.css("position"),width:this.element.outerWidth(),height:this.element.outerHeight(),top:this.element.css("top"),left:this.element.css("left")})),this.element=this.element.parent().data("ui-resizable",this.element.resizable("instance")),this.elementIsWrapper=!0,this.element.css({marginLeft:this.originalElement.css("marginLeft"),marginTop:this.originalElement.css("marginTop"),marginRight:this.originalElement.css("marginRight"),marginBottom:this.originalElement.css("marginBottom")}),this.originalElement.css({marginLeft:0,marginTop:0,marginRight:0,marginBottom:0}),this.originalResizeStyle=this.originalElement.css("resize"),this.originalElement.css("resize","none"),this._proportionallyResizeElements.push(this.originalElement.css({position:"static",zoom:1,display:"block"})),this.originalElement.css({margin:this.originalElement.css("margin")}),this._proportionallyResize()),this.handles=r.handles||(e(".ui-resizable-handle",this.element).length?{n:".ui-resizable-n",e:".ui-resizable-e",s:".ui-resizable-s",w:".ui-resizable-w",se:".ui-resizable-se",sw:".ui-resizable-sw",ne:".ui-resizable-ne",nw:".ui-resizable-nw"}:"e,s,se"),this._handles=e(),this.handles.constructor===String)for("all"===this.handles&&(this.handles="n,e,s,w,se,sw,ne,nw"),t=this.handles.split(","),this.handles={},i=0;t.length>i;i++)s=e.trim(t[i]),a="ui-resizable-"+s,n=e("<div class='ui-resizable-handle "+a+"'></div>"),n.css({zIndex:r.zIndex}),"se"===s&&n.addClass("ui-icon ui-icon-gripsmall-diagonal-se"),this.handles[s]=".ui-resizable-"+s,this.element.append(n);this._renderAxis=function(t){var i,s,n,a;t=t||this.element;for(i in this.handles)this.handles[i].constructor===String?this.handles[i]=this.element.children(this.handles[i]).first().show():(this.handles[i].jquery||this.handles[i].nodeType)&&(this.handles[i]=e(this.handles[i]),this._on(this.handles[i],{mousedown:o._mouseDown})),this.elementIsWrapper&&this.originalElement[0].nodeName.match(/^(textarea|input|select|button)$/i)&&(s=e(this.handles[i],this.element),a=/sw|ne|nw|se|n|s/.test(i)?s.outerHeight():s.outerWidth(),n=["padding",/ne|nw|n/.test(i)?"Top":/se|sw|s/.test(i)?"Bottom":/^e$/.test(i)?"Right":"Left"].join(""),t.css(n,a),this._proportionallyResize()),this._handles=this._handles.add(this.handles[i])},this._renderAxis(this.element),this._handles=this._handles.add(this.element.find(".ui-resizable-handle")),this._handles.disableSelection(),this._handles.mouseover(function(){o.resizing||(this.className&&(n=this.className.match(/ui-resizable-(se|sw|ne|nw|n|e|s|w)/i)),o.axis=n&&n[1]?n[1]:"se")}),r.autoHide&&(this._handles.hide(),e(this.element).addClass("ui-resizable-autohide").mouseenter(function(){r.disabled||(e(this).removeClass("ui-resizable-autohide"),o._handles.show())}).mouseleave(function(){r.disabled||o.resizing||(e(this).addClass("ui-resizable-autohide"),o._handles.hide())})),this._mouseInit()},_destroy:function(){this._mouseDestroy();var t,i=function(t){e(t).removeClass("ui-resizable ui-resizable-disabled ui-resizable-resizing").removeData("resizable").removeData("ui-resizable").unbind(".resizable").find(".ui-resizable-handle").remove()};return this.elementIsWrapper&&(i(this.element),t=this.element,this.originalElement.css({position:t.css("position"),width:t.outerWidth(),height:t.outerHeight(),top:t.css("top"),left:t.css("left")}).insertAfter(t),t.remove()),this.originalElement.css("resize",this.originalResizeStyle),i(this.originalElement),this},_mouseCapture:function(t){var i,s,n=!1;for(i in this.handles)s=e(this.handles[i])[0],(s===t.target||e.contains(s,t.target))&&(n=!0);return!this.options.disabled&&n},_mouseStart:function(t){var i,s,n,a=this.options,o=this.element;return this.resizing=!0,this._renderProxy(),i=this._num(this.helper.css("left")),s=this._num(this.helper.css("top")),a.containment&&(i+=e(a.containment).scrollLeft()||0,s+=e(a.containment).scrollTop()||0),this.offset=this.helper.offset(),this.position={left:i,top:s},this.size=this._helper?{width:this.helper.width(),height:this.helper.height()}:{width:o.width(),height:o.height()},this.originalSize=this._helper?{width:o.outerWidth(),height:o.outerHeight()}:{width:o.width(),height:o.height()},this.sizeDiff={width:o.outerWidth()-o.width(),height:o.outerHeight()-o.height()},this.originalPosition={left:i,top:s},this.originalMousePosition={left:t.pageX,top:t.pageY},this.aspectRatio="number"==typeof a.aspectRatio?a.aspectRatio:this.originalSize.width/this.originalSize.height||1,n=e(".ui-resizable-"+this.axis).css("cursor"),e("body").css("cursor","auto"===n?this.axis+"-resize":n),o.addClass("ui-resizable-resizing"),this._propagate("start",t),!0},_mouseDrag:function(t){var i,s,n=this.originalMousePosition,a=this.axis,o=t.pageX-n.left||0,r=t.pageY-n.top||0,h=this._change[a];return this._updatePrevProperties(),h?(i=h.apply(this,[t,o,r]),this._updateVirtualBoundaries(t.shiftKey),(this._aspectRatio||t.shiftKey)&&(i=this._updateRatio(i,t)),i=this._respectSize(i,t),this._updateCache(i),this._propagate("resize",t),s=this._applyChanges(),!this._helper&&this._proportionallyResizeElements.length&&this._proportionallyResize(),e.isEmptyObject(s)||(this._updatePrevProperties(),this._trigger("resize",t,this.ui()),this._applyChanges()),!1):!1},_mouseStop:function(t){this.resizing=!1;var i,s,n,a,o,r,h,l=this.options,u=this;return this._helper&&(i=this._proportionallyResizeElements,s=i.length&&/textarea/i.test(i[0].nodeName),n=s&&this._hasScroll(i[0],"left")?0:u.sizeDiff.height,a=s?0:u.sizeDiff.width,o={width:u.helper.width()-a,height:u.helper.height()-n},r=parseInt(u.element.css("left"),10)+(u.position.left-u.originalPosition.left)||null,h=parseInt(u.element.css("top"),10)+(u.position.top-u.originalPosition.top)||null,l.animate||this.element.css(e.extend(o,{top:h,left:r})),u.helper.height(u.size.height),u.helper.width(u.size.width),this._helper&&!l.animate&&this._proportionallyResize()),e("body").css("cursor","auto"),this.element.removeClass("ui-resizable-resizing"),this._propagate("stop",t),this._helper&&this.helper.remove(),!1},_updatePrevProperties:function(){this.prevPosition={top:this.position.top,left:this.position.left},this.prevSize={width:this.size.width,height:this.size.height}},_applyChanges:function(){var e={};return this.position.top!==this.prevPosition.top&&(e.top=this.position.top+"px"),this.position.left!==this.prevPosition.left&&(e.left=this.position.left+"px"),this.size.width!==this.prevSize.width&&(e.width=this.size.width+"px"),this.size.height!==this.prevSize.height&&(e.height=this.size.height+"px"),this.helper.css(e),e},_updateVirtualBoundaries:function(e){var t,i,s,n,a,o=this.options;a={minWidth:this._isNumber(o.minWidth)?o.minWidth:0,maxWidth:this._isNumber(o.maxWidth)?o.maxWidth:1/0,minHeight:this._isNumber(o.minHeight)?o.minHeight:0,maxHeight:this._isNumber(o.maxHeight)?o.maxHeight:1/0},(this._aspectRatio||e)&&(t=a.minHeight*this.aspectRatio,s=a.minWidth/this.aspectRatio,i=a.maxHeight*this.aspectRatio,n=a.maxWidth/this.aspectRatio,t>a.minWidth&&(a.minWidth=t),s>a.minHeight&&(a.minHeight=s),a.maxWidth>i&&(a.maxWidth=i),a.maxHeight>n&&(a.maxHeight=n)),this._vBoundaries=a},_updateCache:function(e){this.offset=this.helper.offset(),this._isNumber(e.left)&&(this.position.left=e.left),this._isNumber(e.top)&&(this.position.top=e.top),this._isNumber(e.height)&&(this.size.height=e.height),this._isNumber(e.width)&&(this.size.width=e.width)},_updateRatio:function(e){var t=this.position,i=this.size,s=this.axis;return this._isNumber(e.height)?e.width=e.height*this.aspectRatio:this._isNumber(e.width)&&(e.height=e.width/this.aspectRatio),"sw"===s&&(e.left=t.left+(i.width-e.width),e.top=null),"nw"===s&&(e.top=t.top+(i.height-e.height),e.left=t.left+(i.width-e.width)),e},_respectSize:function(e){var t=this._vBoundaries,i=this.axis,s=this._isNumber(e.width)&&t.maxWidth&&t.maxWidth<e.width,n=this._isNumber(e.height)&&t.maxHeight&&t.maxHeight<e.height,a=this._isNumber(e.width)&&t.minWidth&&t.minWidth>e.width,o=this._isNumber(e.height)&&t.minHeight&&t.minHeight>e.height,r=this.originalPosition.left+this.originalSize.width,h=this.position.top+this.size.height,l=/sw|nw|w/.test(i),u=/nw|ne|n/.test(i);return a&&(e.width=t.minWidth),o&&(e.height=t.minHeight),s&&(e.width=t.maxWidth),n&&(e.height=t.maxHeight),a&&l&&(e.left=r-t.minWidth),s&&l&&(e.left=r-t.maxWidth),o&&u&&(e.top=h-t.minHeight),n&&u&&(e.top=h-t.maxHeight),e.width||e.height||e.left||!e.top?e.width||e.height||e.top||!e.left||(e.left=null):e.top=null,e},_getPaddingPlusBorderDimensions:function(e){for(var t=0,i=[],s=[e.css("borderTopWidth"),e.css("borderRightWidth"),e.css("borderBottomWidth"),e.css("borderLeftWidth")],n=[e.css("paddingTop"),e.css("paddingRight"),e.css("paddingBottom"),e.css("paddingLeft")];4>t;t++)i[t]=parseInt(s[t],10)||0,i[t]+=parseInt(n[t],10)||0;return{height:i[0]+i[2],width:i[1]+i[3]}},_proportionallyResize:function(){if(this._proportionallyResizeElements.length)for(var e,t=0,i=this.helper||this.element;this._proportionallyResizeElements.length>t;t++)e=this._proportionallyResizeElements[t],this.outerDimensions||(this.outerDimensions=this._getPaddingPlusBorderDimensions(e)),e.css({height:i.height()-this.outerDimensions.height||0,width:i.width()-this.outerDimensions.width||0})},_renderProxy:function(){var t=this.element,i=this.options;this.elementOffset=t.offset(),this._helper?(this.helper=this.helper||e("<div style='overflow:hidden;'></div>"),this.helper.addClass(this._helper).css({width:this.element.outerWidth()-1,height:this.element.outerHeight()-1,position:"absolute",left:this.elementOffset.left+"px",top:this.elementOffset.top+"px",zIndex:++i.zIndex}),this.helper.appendTo("body").disableSelection()):this.helper=this.element},_change:{e:function(e,t){return{width:this.originalSize.width+t}},w:function(e,t){var i=this.originalSize,s=this.originalPosition;return{left:s.left+t,width:i.width-t}},n:function(e,t,i){var s=this.originalSize,n=this.originalPosition;return{top:n.top+i,height:s.height-i}},s:function(e,t,i){return{height:this.originalSize.height+i}},se:function(t,i,s){return e.extend(this._change.s.apply(this,arguments),this._change.e.apply(this,[t,i,s]))},sw:function(t,i,s){return e.extend(this._change.s.apply(this,arguments),this._change.w.apply(this,[t,i,s]))},ne:function(t,i,s){return e.extend(this._change.n.apply(this,arguments),this._change.e.apply(this,[t,i,s]))},nw:function(t,i,s){return e.extend(this._change.n.apply(this,arguments),this._change.w.apply(this,[t,i,s]))}},_propagate:function(t,i){e.ui.plugin.call(this,t,[i,this.ui()]),"resize"!==t&&this._trigger(t,i,this.ui())},plugins:{},ui:function(){return{originalElement:this.originalElement,element:this.element,helper:this.helper,position:this.position,size:this.size,originalSize:this.originalSize,originalPosition:this.originalPosition}}}),e.ui.plugin.add("resizable","animate",{stop:function(t){var i=e(this).resizable("instance"),s=i.options,n=i._proportionallyResizeElements,a=n.length&&/textarea/i.test(n[0].nodeName),o=a&&i._hasScroll(n[0],"left")?0:i.sizeDiff.height,r=a?0:i.sizeDiff.width,h={width:i.size.width-r,height:i.size.height-o},l=parseInt(i.element.css("left"),10)+(i.position.left-i.originalPosition.left)||null,u=parseInt(i.element.css("top"),10)+(i.position.top-i.originalPosition.top)||null;i.element.animate(e.extend(h,u&&l?{top:u,left:l}:{}),{duration:s.animateDuration,easing:s.animateEasing,step:function(){var s={width:parseInt(i.element.css("width"),10),height:parseInt(i.element.css("height"),10),top:parseInt(i.element.css("top"),10),left:parseInt(i.element.css("left"),10)};n&&n.length&&e(n[0]).css({width:s.width,height:s.height}),i._updateCache(s),i._propagate("resize",t)}})}}),e.ui.plugin.add("resizable","containment",{start:function(){var t,i,s,n,a,o,r,h=e(this).resizable("instance"),l=h.options,u=h.element,d=l.containment,c=d instanceof e?d.get(0):/parent/.test(d)?u.parent().get(0):d;c&&(h.containerElement=e(c),/document/.test(d)||d===document?(h.containerOffset={left:0,top:0},h.containerPosition={left:0,top:0},h.parentData={element:e(document),left:0,top:0,width:e(document).width(),height:e(document).height()||document.body.parentNode.scrollHeight}):(t=e(c),i=[],e(["Top","Right","Left","Bottom"]).each(function(e,s){i[e]=h._num(t.css("padding"+s))}),h.containerOffset=t.offset(),h.containerPosition=t.position(),h.containerSize={height:t.innerHeight()-i[3],width:t.innerWidth()-i[1]},s=h.containerOffset,n=h.containerSize.height,a=h.containerSize.width,o=h._hasScroll(c,"left")?c.scrollWidth:a,r=h._hasScroll(c)?c.scrollHeight:n,h.parentData={element:c,left:s.left,top:s.top,width:o,height:r}))},resize:function(t){var i,s,n,a,o=e(this).resizable("instance"),r=o.options,h=o.containerOffset,l=o.position,u=o._aspectRatio||t.shiftKey,d={top:0,left:0},c=o.containerElement,p=!0;c[0]!==document&&/static/.test(c.css("position"))&&(d=h),l.left<(o._helper?h.left:0)&&(o.size.width=o.size.width+(o._helper?o.position.left-h.left:o.position.left-d.left),u&&(o.size.height=o.size.width/o.aspectRatio,p=!1),o.position.left=r.helper?h.left:0),l.top<(o._helper?h.top:0)&&(o.size.height=o.size.height+(o._helper?o.position.top-h.top:o.position.top),u&&(o.size.width=o.size.height*o.aspectRatio,p=!1),o.position.top=o._helper?h.top:0),n=o.containerElement.get(0)===o.element.parent().get(0),a=/relative|absolute/.test(o.containerElement.css("position")),n&&a?(o.offset.left=o.parentData.left+o.position.left,o.offset.top=o.parentData.top+o.position.top):(o.offset.left=o.element.offset().left,o.offset.top=o.element.offset().top),i=Math.abs(o.sizeDiff.width+(o._helper?o.offset.left-d.left:o.offset.left-h.left)),s=Math.abs(o.sizeDiff.height+(o._helper?o.offset.top-d.top:o.offset.top-h.top)),i+o.size.width>=o.parentData.width&&(o.size.width=o.parentData.width-i,u&&(o.size.height=o.size.width/o.aspectRatio,p=!1)),s+o.size.height>=o.parentData.height&&(o.size.height=o.parentData.height-s,u&&(o.size.width=o.size.height*o.aspectRatio,p=!1)),p||(o.position.left=o.prevPosition.left,o.position.top=o.prevPosition.top,o.size.width=o.prevSize.width,o.size.height=o.prevSize.height)},stop:function(){var t=e(this).resizable("instance"),i=t.options,s=t.containerOffset,n=t.containerPosition,a=t.containerElement,o=e(t.helper),r=o.offset(),h=o.outerWidth()-t.sizeDiff.width,l=o.outerHeight()-t.sizeDiff.height;t._helper&&!i.animate&&/relative/.test(a.css("position"))&&e(this).css({left:r.left-n.left-s.left,width:h,height:l}),t._helper&&!i.animate&&/static/.test(a.css("position"))&&e(this).css({left:r.left-n.left-s.left,width:h,height:l})}}),e.ui.plugin.add("resizable","alsoResize",{start:function(){var t=e(this).resizable("instance"),i=t.options;e(i.alsoResize).each(function(){var t=e(this);t.data("ui-resizable-alsoresize",{width:parseInt(t.width(),10),height:parseInt(t.height(),10),left:parseInt(t.css("left"),10),top:parseInt(t.css("top"),10)})})},resize:function(t,i){var s=e(this).resizable("instance"),n=s.options,a=s.originalSize,o=s.originalPosition,r={height:s.size.height-a.height||0,width:s.size.width-a.width||0,top:s.position.top-o.top||0,left:s.position.left-o.left||0};e(n.alsoResize).each(function(){var t=e(this),s=e(this).data("ui-resizable-alsoresize"),n={},a=t.parents(i.originalElement[0]).length?["width","height"]:["width","height","top","left"];e.each(a,function(e,t){var i=(s[t]||0)+(r[t]||0);i&&i>=0&&(n[t]=i||null)}),t.css(n)})},stop:function(){e(this).removeData("resizable-alsoresize")}}),e.ui.plugin.add("resizable","ghost",{start:function(){var t=e(this).resizable("instance"),i=t.options,s=t.size;t.ghost=t.originalElement.clone(),t.ghost.css({opacity:.25,display:"block",position:"relative",height:s.height,width:s.width,margin:0,left:0,top:0}).addClass("ui-resizable-ghost").addClass("string"==typeof i.ghost?i.ghost:""),t.ghost.appendTo(t.helper)},resize:function(){var t=e(this).resizable("instance");t.ghost&&t.ghost.css({position:"relative",height:t.size.height,width:t.size.width})},stop:function(){var t=e(this).resizable("instance");t.ghost&&t.helper&&t.helper.get(0).removeChild(t.ghost.get(0))}}),e.ui.plugin.add("resizable","grid",{resize:function(){var t,i=e(this).resizable("instance"),s=i.options,n=i.size,a=i.originalSize,o=i.originalPosition,r=i.axis,h="number"==typeof s.grid?[s.grid,s.grid]:s.grid,l=h[0]||1,u=h[1]||1,d=Math.round((n.width-a.width)/l)*l,c=Math.round((n.height-a.height)/u)*u,p=a.width+d,f=a.height+c,m=s.maxWidth&&p>s.maxWidth,g=s.maxHeight&&f>s.maxHeight,v=s.minWidth&&s.minWidth>p,y=s.minHeight&&s.minHeight>f;s.grid=h,v&&(p+=l),y&&(f+=u),m&&(p-=l),g&&(f-=u),/^(se|s|e)$/.test(r)?(i.size.width=p,i.size.height=f):/^(ne)$/.test(r)?(i.size.width=p,i.size.height=f,i.position.top=o.top-c):/^(sw)$/.test(r)?(i.size.width=p,i.size.height=f,i.position.left=o.left-d):((0>=f-u||0>=p-l)&&(t=i._getPaddingPlusBorderDimensions(this)),f-u>0?(i.size.height=f,i.position.top=o.top-c):(f=u-t.height,i.size.height=f,i.position.top=o.top+a.height-f),p-l>0?(i.size.width=p,i.position.left=o.left-d):(p=l-t.width,i.size.width=p,i.position.left=o.left+a.width-p))}}),e.ui.resizable,e.widget("ui.selectable",e.ui.mouse,{version:"1.11.4",options:{appendTo:"body",autoRefresh:!0,distance:0,filter:"*",tolerance:"touch",selected:null,selecting:null,start:null,stop:null,unselected:null,unselecting:null},_create:function(){var t,i=this;this.element.addClass("ui-selectable"),this.dragged=!1,this.refresh=function(){t=e(i.options.filter,i.element[0]),t.addClass("ui-selectee"),t.each(function(){var t=e(this),i=t.offset();e.data(this,"selectable-item",{element:this,$element:t,left:i.left,top:i.top,right:i.left+t.outerWidth(),bottom:i.top+t.outerHeight(),startselected:!1,selected:t.hasClass("ui-selected"),selecting:t.hasClass("ui-selecting"),unselecting:t.hasClass("ui-unselecting")})})},this.refresh(),this.selectees=t.addClass("ui-selectee"),this._mouseInit(),this.helper=e("<div class='ui-selectable-helper'></div>")},_destroy:function(){this.selectees.removeClass("ui-selectee").removeData("selectable-item"),this.element.removeClass("ui-selectable ui-selectable-disabled"),this._mouseDestroy()},_mouseStart:function(t){var i=this,s=this.options;this.opos=[t.pageX,t.pageY],this.options.disabled||(this.selectees=e(s.filter,this.element[0]),this._trigger("start",t),e(s.appendTo).append(this.helper),this.helper.css({left:t.pageX,top:t.pageY,width:0,height:0}),s.autoRefresh&&this.refresh(),this.selectees.filter(".ui-selected").each(function(){var s=e.data(this,"selectable-item");s.startselected=!0,t.metaKey||t.ctrlKey||(s.$element.removeClass("ui-selected"),s.selected=!1,s.$element.addClass("ui-unselecting"),s.unselecting=!0,i._trigger("unselecting",t,{unselecting:s.element}))}),e(t.target).parents().addBack().each(function(){var s,n=e.data(this,"selectable-item");return n?(s=!t.metaKey&&!t.ctrlKey||!n.$element.hasClass("ui-selected"),n.$element.removeClass(s?"ui-unselecting":"ui-selected").addClass(s?"ui-selecting":"ui-unselecting"),n.unselecting=!s,n.selecting=s,n.selected=s,s?i._trigger("selecting",t,{selecting:n.element}):i._trigger("unselecting",t,{unselecting:n.element}),!1):void 0}))},_mouseDrag:function(t){if(this.dragged=!0,!this.options.disabled){var i,s=this,n=this.options,a=this.opos[0],o=this.opos[1],r=t.pageX,h=t.pageY;return a>r&&(i=r,r=a,a=i),o>h&&(i=h,h=o,o=i),this.helper.css({left:a,top:o,width:r-a,height:h-o}),this.selectees.each(function(){var i=e.data(this,"selectable-item"),l=!1;
i&&i.element!==s.element[0]&&("touch"===n.tolerance?l=!(i.left>r||a>i.right||i.top>h||o>i.bottom):"fit"===n.tolerance&&(l=i.left>a&&r>i.right&&i.top>o&&h>i.bottom),l?(i.selected&&(i.$element.removeClass("ui-selected"),i.selected=!1),i.unselecting&&(i.$element.removeClass("ui-unselecting"),i.unselecting=!1),i.selecting||(i.$element.addClass("ui-selecting"),i.selecting=!0,s._trigger("selecting",t,{selecting:i.element}))):(i.selecting&&((t.metaKey||t.ctrlKey)&&i.startselected?(i.$element.removeClass("ui-selecting"),i.selecting=!1,i.$element.addClass("ui-selected"),i.selected=!0):(i.$element.removeClass("ui-selecting"),i.selecting=!1,i.startselected&&(i.$element.addClass("ui-unselecting"),i.unselecting=!0),s._trigger("unselecting",t,{unselecting:i.element}))),i.selected&&(t.metaKey||t.ctrlKey||i.startselected||(i.$element.removeClass("ui-selected"),i.selected=!1,i.$element.addClass("ui-unselecting"),i.unselecting=!0,s._trigger("unselecting",t,{unselecting:i.element})))))}),!1}},_mouseStop:function(t){var i=this;return this.dragged=!1,e(".ui-unselecting",this.element[0]).each(function(){var s=e.data(this,"selectable-item");s.$element.removeClass("ui-unselecting"),s.unselecting=!1,s.startselected=!1,i._trigger("unselected",t,{unselected:s.element})}),e(".ui-selecting",this.element[0]).each(function(){var s=e.data(this,"selectable-item");s.$element.removeClass("ui-selecting").addClass("ui-selected"),s.selecting=!1,s.selected=!0,s.startselected=!0,i._trigger("selected",t,{selected:s.element})}),this._trigger("stop",t),this.helper.remove(),!1}}),e.widget("ui.sortable",e.ui.mouse,{version:"1.11.4",widgetEventPrefix:"sort",ready:!1,options:{appendTo:"parent",axis:!1,connectWith:!1,containment:!1,cursor:"auto",cursorAt:!1,dropOnEmpty:!0,forcePlaceholderSize:!1,forceHelperSize:!1,grid:!1,handle:!1,helper:"original",items:"> *",opacity:!1,placeholder:!1,revert:!1,scroll:!0,scrollSensitivity:20,scrollSpeed:20,scope:"default",tolerance:"intersect",zIndex:1e3,activate:null,beforeStop:null,change:null,deactivate:null,out:null,over:null,receive:null,remove:null,sort:null,start:null,stop:null,update:null},_isOverAxis:function(e,t,i){return e>=t&&t+i>e},_isFloating:function(e){return/left|right/.test(e.css("float"))||/inline|table-cell/.test(e.css("display"))},_create:function(){this.containerCache={},this.element.addClass("ui-sortable"),this.refresh(),this.offset=this.element.offset(),this._mouseInit(),this._setHandleClassName(),this.ready=!0},_setOption:function(e,t){this._super(e,t),"handle"===e&&this._setHandleClassName()},_setHandleClassName:function(){this.element.find(".ui-sortable-handle").removeClass("ui-sortable-handle"),e.each(this.items,function(){(this.instance.options.handle?this.item.find(this.instance.options.handle):this.item).addClass("ui-sortable-handle")})},_destroy:function(){this.element.removeClass("ui-sortable ui-sortable-disabled").find(".ui-sortable-handle").removeClass("ui-sortable-handle"),this._mouseDestroy();for(var e=this.items.length-1;e>=0;e--)this.items[e].item.removeData(this.widgetName+"-item");return this},_mouseCapture:function(t,i){var s=null,n=!1,a=this;return this.reverting?!1:this.options.disabled||"static"===this.options.type?!1:(this._refreshItems(t),e(t.target).parents().each(function(){return e.data(this,a.widgetName+"-item")===a?(s=e(this),!1):void 0}),e.data(t.target,a.widgetName+"-item")===a&&(s=e(t.target)),s?!this.options.handle||i||(e(this.options.handle,s).find("*").addBack().each(function(){this===t.target&&(n=!0)}),n)?(this.currentItem=s,this._removeCurrentsFromItems(),!0):!1:!1)},_mouseStart:function(t,i,s){var n,a,o=this.options;if(this.currentContainer=this,this.refreshPositions(),this.helper=this._createHelper(t),this._cacheHelperProportions(),this._cacheMargins(),this.scrollParent=this.helper.scrollParent(),this.offset=this.currentItem.offset(),this.offset={top:this.offset.top-this.margins.top,left:this.offset.left-this.margins.left},e.extend(this.offset,{click:{left:t.pageX-this.offset.left,top:t.pageY-this.offset.top},parent:this._getParentOffset(),relative:this._getRelativeOffset()}),this.helper.css("position","absolute"),this.cssPosition=this.helper.css("position"),this.originalPosition=this._generatePosition(t),this.originalPageX=t.pageX,this.originalPageY=t.pageY,o.cursorAt&&this._adjustOffsetFromHelper(o.cursorAt),this.domPosition={prev:this.currentItem.prev()[0],parent:this.currentItem.parent()[0]},this.helper[0]!==this.currentItem[0]&&this.currentItem.hide(),this._createPlaceholder(),o.containment&&this._setContainment(),o.cursor&&"auto"!==o.cursor&&(a=this.document.find("body"),this.storedCursor=a.css("cursor"),a.css("cursor",o.cursor),this.storedStylesheet=e("<style>*{ cursor: "+o.cursor+" !important; }</style>").appendTo(a)),o.opacity&&(this.helper.css("opacity")&&(this._storedOpacity=this.helper.css("opacity")),this.helper.css("opacity",o.opacity)),o.zIndex&&(this.helper.css("zIndex")&&(this._storedZIndex=this.helper.css("zIndex")),this.helper.css("zIndex",o.zIndex)),this.scrollParent[0]!==this.document[0]&&"HTML"!==this.scrollParent[0].tagName&&(this.overflowOffset=this.scrollParent.offset()),this._trigger("start",t,this._uiHash()),this._preserveHelperProportions||this._cacheHelperProportions(),!s)for(n=this.containers.length-1;n>=0;n--)this.containers[n]._trigger("activate",t,this._uiHash(this));return e.ui.ddmanager&&(e.ui.ddmanager.current=this),e.ui.ddmanager&&!o.dropBehaviour&&e.ui.ddmanager.prepareOffsets(this,t),this.dragging=!0,this.helper.addClass("ui-sortable-helper"),this._mouseDrag(t),!0},_mouseDrag:function(t){var i,s,n,a,o=this.options,r=!1;for(this.position=this._generatePosition(t),this.positionAbs=this._convertPositionTo("absolute"),this.lastPositionAbs||(this.lastPositionAbs=this.positionAbs),this.options.scroll&&(this.scrollParent[0]!==this.document[0]&&"HTML"!==this.scrollParent[0].tagName?(this.overflowOffset.top+this.scrollParent[0].offsetHeight-t.pageY<o.scrollSensitivity?this.scrollParent[0].scrollTop=r=this.scrollParent[0].scrollTop+o.scrollSpeed:t.pageY-this.overflowOffset.top<o.scrollSensitivity&&(this.scrollParent[0].scrollTop=r=this.scrollParent[0].scrollTop-o.scrollSpeed),this.overflowOffset.left+this.scrollParent[0].offsetWidth-t.pageX<o.scrollSensitivity?this.scrollParent[0].scrollLeft=r=this.scrollParent[0].scrollLeft+o.scrollSpeed:t.pageX-this.overflowOffset.left<o.scrollSensitivity&&(this.scrollParent[0].scrollLeft=r=this.scrollParent[0].scrollLeft-o.scrollSpeed)):(t.pageY-this.document.scrollTop()<o.scrollSensitivity?r=this.document.scrollTop(this.document.scrollTop()-o.scrollSpeed):this.window.height()-(t.pageY-this.document.scrollTop())<o.scrollSensitivity&&(r=this.document.scrollTop(this.document.scrollTop()+o.scrollSpeed)),t.pageX-this.document.scrollLeft()<o.scrollSensitivity?r=this.document.scrollLeft(this.document.scrollLeft()-o.scrollSpeed):this.window.width()-(t.pageX-this.document.scrollLeft())<o.scrollSensitivity&&(r=this.document.scrollLeft(this.document.scrollLeft()+o.scrollSpeed))),r!==!1&&e.ui.ddmanager&&!o.dropBehaviour&&e.ui.ddmanager.prepareOffsets(this,t)),this.positionAbs=this._convertPositionTo("absolute"),this.options.axis&&"y"===this.options.axis||(this.helper[0].style.left=this.position.left+"px"),this.options.axis&&"x"===this.options.axis||(this.helper[0].style.top=this.position.top+"px"),i=this.items.length-1;i>=0;i--)if(s=this.items[i],n=s.item[0],a=this._intersectsWithPointer(s),a&&s.instance===this.currentContainer&&n!==this.currentItem[0]&&this.placeholder[1===a?"next":"prev"]()[0]!==n&&!e.contains(this.placeholder[0],n)&&("semi-dynamic"===this.options.type?!e.contains(this.element[0],n):!0)){if(this.direction=1===a?"down":"up","pointer"!==this.options.tolerance&&!this._intersectsWithSides(s))break;this._rearrange(t,s),this._trigger("change",t,this._uiHash());break}return this._contactContainers(t),e.ui.ddmanager&&e.ui.ddmanager.drag(this,t),this._trigger("sort",t,this._uiHash()),this.lastPositionAbs=this.positionAbs,!1},_mouseStop:function(t,i){if(t){if(e.ui.ddmanager&&!this.options.dropBehaviour&&e.ui.ddmanager.drop(this,t),this.options.revert){var s=this,n=this.placeholder.offset(),a=this.options.axis,o={};a&&"x"!==a||(o.left=n.left-this.offset.parent.left-this.margins.left+(this.offsetParent[0]===this.document[0].body?0:this.offsetParent[0].scrollLeft)),a&&"y"!==a||(o.top=n.top-this.offset.parent.top-this.margins.top+(this.offsetParent[0]===this.document[0].body?0:this.offsetParent[0].scrollTop)),this.reverting=!0,e(this.helper).animate(o,parseInt(this.options.revert,10)||500,function(){s._clear(t)})}else this._clear(t,i);return!1}},cancel:function(){if(this.dragging){this._mouseUp({target:null}),"original"===this.options.helper?this.currentItem.css(this._storedCSS).removeClass("ui-sortable-helper"):this.currentItem.show();for(var t=this.containers.length-1;t>=0;t--)this.containers[t]._trigger("deactivate",null,this._uiHash(this)),this.containers[t].containerCache.over&&(this.containers[t]._trigger("out",null,this._uiHash(this)),this.containers[t].containerCache.over=0)}return this.placeholder&&(this.placeholder[0].parentNode&&this.placeholder[0].parentNode.removeChild(this.placeholder[0]),"original"!==this.options.helper&&this.helper&&this.helper[0].parentNode&&this.helper.remove(),e.extend(this,{helper:null,dragging:!1,reverting:!1,_noFinalSort:null}),this.domPosition.prev?e(this.domPosition.prev).after(this.currentItem):e(this.domPosition.parent).prepend(this.currentItem)),this},serialize:function(t){var i=this._getItemsAsjQuery(t&&t.connected),s=[];return t=t||{},e(i).each(function(){var i=(e(t.item||this).attr(t.attribute||"id")||"").match(t.expression||/(.+)[\-=_](.+)/);i&&s.push((t.key||i[1]+"[]")+"="+(t.key&&t.expression?i[1]:i[2]))}),!s.length&&t.key&&s.push(t.key+"="),s.join("&")},toArray:function(t){var i=this._getItemsAsjQuery(t&&t.connected),s=[];return t=t||{},i.each(function(){s.push(e(t.item||this).attr(t.attribute||"id")||"")}),s},_intersectsWith:function(e){var t=this.positionAbs.left,i=t+this.helperProportions.width,s=this.positionAbs.top,n=s+this.helperProportions.height,a=e.left,o=a+e.width,r=e.top,h=r+e.height,l=this.offset.click.top,u=this.offset.click.left,d="x"===this.options.axis||s+l>r&&h>s+l,c="y"===this.options.axis||t+u>a&&o>t+u,p=d&&c;return"pointer"===this.options.tolerance||this.options.forcePointerForContainers||"pointer"!==this.options.tolerance&&this.helperProportions[this.floating?"width":"height"]>e[this.floating?"width":"height"]?p:t+this.helperProportions.width/2>a&&o>i-this.helperProportions.width/2&&s+this.helperProportions.height/2>r&&h>n-this.helperProportions.height/2},_intersectsWithPointer:function(e){var t="x"===this.options.axis||this._isOverAxis(this.positionAbs.top+this.offset.click.top,e.top,e.height),i="y"===this.options.axis||this._isOverAxis(this.positionAbs.left+this.offset.click.left,e.left,e.width),s=t&&i,n=this._getDragVerticalDirection(),a=this._getDragHorizontalDirection();return s?this.floating?a&&"right"===a||"down"===n?2:1:n&&("down"===n?2:1):!1},_intersectsWithSides:function(e){var t=this._isOverAxis(this.positionAbs.top+this.offset.click.top,e.top+e.height/2,e.height),i=this._isOverAxis(this.positionAbs.left+this.offset.click.left,e.left+e.width/2,e.width),s=this._getDragVerticalDirection(),n=this._getDragHorizontalDirection();return this.floating&&n?"right"===n&&i||"left"===n&&!i:s&&("down"===s&&t||"up"===s&&!t)},_getDragVerticalDirection:function(){var e=this.positionAbs.top-this.lastPositionAbs.top;return 0!==e&&(e>0?"down":"up")},_getDragHorizontalDirection:function(){var e=this.positionAbs.left-this.lastPositionAbs.left;return 0!==e&&(e>0?"right":"left")},refresh:function(e){return this._refreshItems(e),this._setHandleClassName(),this.refreshPositions(),this},_connectWith:function(){var e=this.options;return e.connectWith.constructor===String?[e.connectWith]:e.connectWith},_getItemsAsjQuery:function(t){function i(){r.push(this)}var s,n,a,o,r=[],h=[],l=this._connectWith();if(l&&t)for(s=l.length-1;s>=0;s--)for(a=e(l[s],this.document[0]),n=a.length-1;n>=0;n--)o=e.data(a[n],this.widgetFullName),o&&o!==this&&!o.options.disabled&&h.push([e.isFunction(o.options.items)?o.options.items.call(o.element):e(o.options.items,o.element).not(".ui-sortable-helper").not(".ui-sortable-placeholder"),o]);for(h.push([e.isFunction(this.options.items)?this.options.items.call(this.element,null,{options:this.options,item:this.currentItem}):e(this.options.items,this.element).not(".ui-sortable-helper").not(".ui-sortable-placeholder"),this]),s=h.length-1;s>=0;s--)h[s][0].each(i);return e(r)},_removeCurrentsFromItems:function(){var t=this.currentItem.find(":data("+this.widgetName+"-item)");this.items=e.grep(this.items,function(e){for(var i=0;t.length>i;i++)if(t[i]===e.item[0])return!1;return!0})},_refreshItems:function(t){this.items=[],this.containers=[this];var i,s,n,a,o,r,h,l,u=this.items,d=[[e.isFunction(this.options.items)?this.options.items.call(this.element[0],t,{item:this.currentItem}):e(this.options.items,this.element),this]],c=this._connectWith();if(c&&this.ready)for(i=c.length-1;i>=0;i--)for(n=e(c[i],this.document[0]),s=n.length-1;s>=0;s--)a=e.data(n[s],this.widgetFullName),a&&a!==this&&!a.options.disabled&&(d.push([e.isFunction(a.options.items)?a.options.items.call(a.element[0],t,{item:this.currentItem}):e(a.options.items,a.element),a]),this.containers.push(a));for(i=d.length-1;i>=0;i--)for(o=d[i][1],r=d[i][0],s=0,l=r.length;l>s;s++)h=e(r[s]),h.data(this.widgetName+"-item",o),u.push({item:h,instance:o,width:0,height:0,left:0,top:0})},refreshPositions:function(t){this.floating=this.items.length?"x"===this.options.axis||this._isFloating(this.items[0].item):!1,this.offsetParent&&this.helper&&(this.offset.parent=this._getParentOffset());var i,s,n,a;for(i=this.items.length-1;i>=0;i--)s=this.items[i],s.instance!==this.currentContainer&&this.currentContainer&&s.item[0]!==this.currentItem[0]||(n=this.options.toleranceElement?e(this.options.toleranceElement,s.item):s.item,t||(s.width=n.outerWidth(),s.height=n.outerHeight()),a=n.offset(),s.left=a.left,s.top=a.top);if(this.options.custom&&this.options.custom.refreshContainers)this.options.custom.refreshContainers.call(this);else for(i=this.containers.length-1;i>=0;i--)a=this.containers[i].element.offset(),this.containers[i].containerCache.left=a.left,this.containers[i].containerCache.top=a.top,this.containers[i].containerCache.width=this.containers[i].element.outerWidth(),this.containers[i].containerCache.height=this.containers[i].element.outerHeight();return this},_createPlaceholder:function(t){t=t||this;var i,s=t.options;s.placeholder&&s.placeholder.constructor!==String||(i=s.placeholder,s.placeholder={element:function(){var s=t.currentItem[0].nodeName.toLowerCase(),n=e("<"+s+">",t.document[0]).addClass(i||t.currentItem[0].className+" ui-sortable-placeholder").removeClass("ui-sortable-helper");return"tbody"===s?t._createTrPlaceholder(t.currentItem.find("tr").eq(0),e("<tr>",t.document[0]).appendTo(n)):"tr"===s?t._createTrPlaceholder(t.currentItem,n):"img"===s&&n.attr("src",t.currentItem.attr("src")),i||n.css("visibility","hidden"),n},update:function(e,n){(!i||s.forcePlaceholderSize)&&(n.height()||n.height(t.currentItem.innerHeight()-parseInt(t.currentItem.css("paddingTop")||0,10)-parseInt(t.currentItem.css("paddingBottom")||0,10)),n.width()||n.width(t.currentItem.innerWidth()-parseInt(t.currentItem.css("paddingLeft")||0,10)-parseInt(t.currentItem.css("paddingRight")||0,10)))}}),t.placeholder=e(s.placeholder.element.call(t.element,t.currentItem)),t.currentItem.after(t.placeholder),s.placeholder.update(t,t.placeholder)},_createTrPlaceholder:function(t,i){var s=this;t.children().each(function(){e("<td>&#160;</td>",s.document[0]).attr("colspan",e(this).attr("colspan")||1).appendTo(i)})},_contactContainers:function(t){var i,s,n,a,o,r,h,l,u,d,c=null,p=null;for(i=this.containers.length-1;i>=0;i--)if(!e.contains(this.currentItem[0],this.containers[i].element[0]))if(this._intersectsWith(this.containers[i].containerCache)){if(c&&e.contains(this.containers[i].element[0],c.element[0]))continue;c=this.containers[i],p=i}else this.containers[i].containerCache.over&&(this.containers[i]._trigger("out",t,this._uiHash(this)),this.containers[i].containerCache.over=0);if(c)if(1===this.containers.length)this.containers[p].containerCache.over||(this.containers[p]._trigger("over",t,this._uiHash(this)),this.containers[p].containerCache.over=1);else{for(n=1e4,a=null,u=c.floating||this._isFloating(this.currentItem),o=u?"left":"top",r=u?"width":"height",d=u?"clientX":"clientY",s=this.items.length-1;s>=0;s--)e.contains(this.containers[p].element[0],this.items[s].item[0])&&this.items[s].item[0]!==this.currentItem[0]&&(h=this.items[s].item.offset()[o],l=!1,t[d]-h>this.items[s][r]/2&&(l=!0),n>Math.abs(t[d]-h)&&(n=Math.abs(t[d]-h),a=this.items[s],this.direction=l?"up":"down"));if(!a&&!this.options.dropOnEmpty)return;if(this.currentContainer===this.containers[p])return this.currentContainer.containerCache.over||(this.containers[p]._trigger("over",t,this._uiHash()),this.currentContainer.containerCache.over=1),void 0;a?this._rearrange(t,a,null,!0):this._rearrange(t,null,this.containers[p].element,!0),this._trigger("change",t,this._uiHash()),this.containers[p]._trigger("change",t,this._uiHash(this)),this.currentContainer=this.containers[p],this.options.placeholder.update(this.currentContainer,this.placeholder),this.containers[p]._trigger("over",t,this._uiHash(this)),this.containers[p].containerCache.over=1}},_createHelper:function(t){var i=this.options,s=e.isFunction(i.helper)?e(i.helper.apply(this.element[0],[t,this.currentItem])):"clone"===i.helper?this.currentItem.clone():this.currentItem;return s.parents("body").length||e("parent"!==i.appendTo?i.appendTo:this.currentItem[0].parentNode)[0].appendChild(s[0]),s[0]===this.currentItem[0]&&(this._storedCSS={width:this.currentItem[0].style.width,height:this.currentItem[0].style.height,position:this.currentItem.css("position"),top:this.currentItem.css("top"),left:this.currentItem.css("left")}),(!s[0].style.width||i.forceHelperSize)&&s.width(this.currentItem.width()),(!s[0].style.height||i.forceHelperSize)&&s.height(this.currentItem.height()),s},_adjustOffsetFromHelper:function(t){"string"==typeof t&&(t=t.split(" ")),e.isArray(t)&&(t={left:+t[0],top:+t[1]||0}),"left"in t&&(this.offset.click.left=t.left+this.margins.left),"right"in t&&(this.offset.click.left=this.helperProportions.width-t.right+this.margins.left),"top"in t&&(this.offset.click.top=t.top+this.margins.top),"bottom"in t&&(this.offset.click.top=this.helperProportions.height-t.bottom+this.margins.top)},_getParentOffset:function(){this.offsetParent=this.helper.offsetParent();var t=this.offsetParent.offset();return"absolute"===this.cssPosition&&this.scrollParent[0]!==this.document[0]&&e.contains(this.scrollParent[0],this.offsetParent[0])&&(t.left+=this.scrollParent.scrollLeft(),t.top+=this.scrollParent.scrollTop()),(this.offsetParent[0]===this.document[0].body||this.offsetParent[0].tagName&&"html"===this.offsetParent[0].tagName.toLowerCase()&&e.ui.ie)&&(t={top:0,left:0}),{top:t.top+(parseInt(this.offsetParent.css("borderTopWidth"),10)||0),left:t.left+(parseInt(this.offsetParent.css("borderLeftWidth"),10)||0)}},_getRelativeOffset:function(){if("relative"===this.cssPosition){var e=this.currentItem.position();return{top:e.top-(parseInt(this.helper.css("top"),10)||0)+this.scrollParent.scrollTop(),left:e.left-(parseInt(this.helper.css("left"),10)||0)+this.scrollParent.scrollLeft()}}return{top:0,left:0}},_cacheMargins:function(){this.margins={left:parseInt(this.currentItem.css("marginLeft"),10)||0,top:parseInt(this.currentItem.css("marginTop"),10)||0}},_cacheHelperProportions:function(){this.helperProportions={width:this.helper.outerWidth(),height:this.helper.outerHeight()}},_setContainment:function(){var t,i,s,n=this.options;"parent"===n.containment&&(n.containment=this.helper[0].parentNode),("document"===n.containment||"window"===n.containment)&&(this.containment=[0-this.offset.relative.left-this.offset.parent.left,0-this.offset.relative.top-this.offset.parent.top,"document"===n.containment?this.document.width():this.window.width()-this.helperProportions.width-this.margins.left,("document"===n.containment?this.document.width():this.window.height()||this.document[0].body.parentNode.scrollHeight)-this.helperProportions.height-this.margins.top]),/^(document|window|parent)$/.test(n.containment)||(t=e(n.containment)[0],i=e(n.containment).offset(),s="hidden"!==e(t).css("overflow"),this.containment=[i.left+(parseInt(e(t).css("borderLeftWidth"),10)||0)+(parseInt(e(t).css("paddingLeft"),10)||0)-this.margins.left,i.top+(parseInt(e(t).css("borderTopWidth"),10)||0)+(parseInt(e(t).css("paddingTop"),10)||0)-this.margins.top,i.left+(s?Math.max(t.scrollWidth,t.offsetWidth):t.offsetWidth)-(parseInt(e(t).css("borderLeftWidth"),10)||0)-(parseInt(e(t).css("paddingRight"),10)||0)-this.helperProportions.width-this.margins.left,i.top+(s?Math.max(t.scrollHeight,t.offsetHeight):t.offsetHeight)-(parseInt(e(t).css("borderTopWidth"),10)||0)-(parseInt(e(t).css("paddingBottom"),10)||0)-this.helperProportions.height-this.margins.top])},_convertPositionTo:function(t,i){i||(i=this.position);var s="absolute"===t?1:-1,n="absolute"!==this.cssPosition||this.scrollParent[0]!==this.document[0]&&e.contains(this.scrollParent[0],this.offsetParent[0])?this.scrollParent:this.offsetParent,a=/(html|body)/i.test(n[0].tagName);return{top:i.top+this.offset.relative.top*s+this.offset.parent.top*s-("fixed"===this.cssPosition?-this.scrollParent.scrollTop():a?0:n.scrollTop())*s,left:i.left+this.offset.relative.left*s+this.offset.parent.left*s-("fixed"===this.cssPosition?-this.scrollParent.scrollLeft():a?0:n.scrollLeft())*s}},_generatePosition:function(t){var i,s,n=this.options,a=t.pageX,o=t.pageY,r="absolute"!==this.cssPosition||this.scrollParent[0]!==this.document[0]&&e.contains(this.scrollParent[0],this.offsetParent[0])?this.scrollParent:this.offsetParent,h=/(html|body)/i.test(r[0].tagName);return"relative"!==this.cssPosition||this.scrollParent[0]!==this.document[0]&&this.scrollParent[0]!==this.offsetParent[0]||(this.offset.relative=this._getRelativeOffset()),this.originalPosition&&(this.containment&&(t.pageX-this.offset.click.left<this.containment[0]&&(a=this.containment[0]+this.offset.click.left),t.pageY-this.offset.click.top<this.containment[1]&&(o=this.containment[1]+this.offset.click.top),t.pageX-this.offset.click.left>this.containment[2]&&(a=this.containment[2]+this.offset.click.left),t.pageY-this.offset.click.top>this.containment[3]&&(o=this.containment[3]+this.offset.click.top)),n.grid&&(i=this.originalPageY+Math.round((o-this.originalPageY)/n.grid[1])*n.grid[1],o=this.containment?i-this.offset.click.top>=this.containment[1]&&i-this.offset.click.top<=this.containment[3]?i:i-this.offset.click.top>=this.containment[1]?i-n.grid[1]:i+n.grid[1]:i,s=this.originalPageX+Math.round((a-this.originalPageX)/n.grid[0])*n.grid[0],a=this.containment?s-this.offset.click.left>=this.containment[0]&&s-this.offset.click.left<=this.containment[2]?s:s-this.offset.click.left>=this.containment[0]?s-n.grid[0]:s+n.grid[0]:s)),{top:o-this.offset.click.top-this.offset.relative.top-this.offset.parent.top+("fixed"===this.cssPosition?-this.scrollParent.scrollTop():h?0:r.scrollTop()),left:a-this.offset.click.left-this.offset.relative.left-this.offset.parent.left+("fixed"===this.cssPosition?-this.scrollParent.scrollLeft():h?0:r.scrollLeft())}},_rearrange:function(e,t,i,s){i?i[0].appendChild(this.placeholder[0]):t.item[0].parentNode.insertBefore(this.placeholder[0],"down"===this.direction?t.item[0]:t.item[0].nextSibling),this.counter=this.counter?++this.counter:1;var n=this.counter;this._delay(function(){n===this.counter&&this.refreshPositions(!s)})},_clear:function(e,t){function i(e,t,i){return function(s){i._trigger(e,s,t._uiHash(t))}}this.reverting=!1;var s,n=[];if(!this._noFinalSort&&this.currentItem.parent().length&&this.placeholder.before(this.currentItem),this._noFinalSort=null,this.helper[0]===this.currentItem[0]){for(s in this._storedCSS)("auto"===this._storedCSS[s]||"static"===this._storedCSS[s])&&(this._storedCSS[s]="");this.currentItem.css(this._storedCSS).removeClass("ui-sortable-helper")}else this.currentItem.show();for(this.fromOutside&&!t&&n.push(function(e){this._trigger("receive",e,this._uiHash(this.fromOutside))}),!this.fromOutside&&this.domPosition.prev===this.currentItem.prev().not(".ui-sortable-helper")[0]&&this.domPosition.parent===this.currentItem.parent()[0]||t||n.push(function(e){this._trigger("update",e,this._uiHash())}),this!==this.currentContainer&&(t||(n.push(function(e){this._trigger("remove",e,this._uiHash())}),n.push(function(e){return function(t){e._trigger("receive",t,this._uiHash(this))}}.call(this,this.currentContainer)),n.push(function(e){return function(t){e._trigger("update",t,this._uiHash(this))}}.call(this,this.currentContainer)))),s=this.containers.length-1;s>=0;s--)t||n.push(i("deactivate",this,this.containers[s])),this.containers[s].containerCache.over&&(n.push(i("out",this,this.containers[s])),this.containers[s].containerCache.over=0);if(this.storedCursor&&(this.document.find("body").css("cursor",this.storedCursor),this.storedStylesheet.remove()),this._storedOpacity&&this.helper.css("opacity",this._storedOpacity),this._storedZIndex&&this.helper.css("zIndex","auto"===this._storedZIndex?"":this._storedZIndex),this.dragging=!1,t||this._trigger("beforeStop",e,this._uiHash()),this.placeholder[0].parentNode.removeChild(this.placeholder[0]),this.cancelHelperRemoval||(this.helper[0]!==this.currentItem[0]&&this.helper.remove(),this.helper=null),!t){for(s=0;n.length>s;s++)n[s].call(this,e);this._trigger("stop",e,this._uiHash())}return this.fromOutside=!1,!this.cancelHelperRemoval},_trigger:function(){e.Widget.prototype._trigger.apply(this,arguments)===!1&&this.cancel()},_uiHash:function(t){var i=t||this;return{helper:i.helper,placeholder:i.placeholder||e([]),position:i.position,originalPosition:i.originalPosition,offset:i.positionAbs,item:i.currentItem,sender:t?t.element:null}}}),e.widget("ui.accordion",{version:"1.11.4",options:{active:0,animate:{},collapsible:!1,event:"click",header:"> li > :first-child,> :not(li):even",heightStyle:"auto",icons:{activeHeader:"ui-icon-triangle-1-s",header:"ui-icon-triangle-1-e"},activate:null,beforeActivate:null},hideProps:{borderTopWidth:"hide",borderBottomWidth:"hide",paddingTop:"hide",paddingBottom:"hide",height:"hide"},showProps:{borderTopWidth:"show",borderBottomWidth:"show",paddingTop:"show",paddingBottom:"show",height:"show"},_create:function(){var t=this.options;this.prevShow=this.prevHide=e(),this.element.addClass("ui-accordion ui-widget ui-helper-reset").attr("role","tablist"),t.collapsible||t.active!==!1&&null!=t.active||(t.active=0),this._processPanels(),0>t.active&&(t.active+=this.headers.length),this._refresh()},_getCreateEventData:function(){return{header:this.active,panel:this.active.length?this.active.next():e()}},_createIcons:function(){var t=this.options.icons;t&&(e("<span>").addClass("ui-accordion-header-icon ui-icon "+t.header).prependTo(this.headers),this.active.children(".ui-accordion-header-icon").removeClass(t.header).addClass(t.activeHeader),this.headers.addClass("ui-accordion-icons"))},_destroyIcons:function(){this.headers.removeClass("ui-accordion-icons").children(".ui-accordion-header-icon").remove()},_destroy:function(){var e;this.element.removeClass("ui-accordion ui-widget ui-helper-reset").removeAttr("role"),this.headers.removeClass("ui-accordion-header ui-accordion-header-active ui-state-default ui-corner-all ui-state-active ui-state-disabled ui-corner-top").removeAttr("role").removeAttr("aria-expanded").removeAttr("aria-selected").removeAttr("aria-controls").removeAttr("tabIndex").removeUniqueId(),this._destroyIcons(),e=this.headers.next().removeClass("ui-helper-reset ui-widget-content ui-corner-bottom ui-accordion-content ui-accordion-content-active ui-state-disabled").css("display","").removeAttr("role").removeAttr("aria-hidden").removeAttr("aria-labelledby").removeUniqueId(),"content"!==this.options.heightStyle&&e.css("height","")},_setOption:function(e,t){return"active"===e?(this._activate(t),void 0):("event"===e&&(this.options.event&&this._off(this.headers,this.options.event),this._setupEvents(t)),this._super(e,t),"collapsible"!==e||t||this.options.active!==!1||this._activate(0),"icons"===e&&(this._destroyIcons(),t&&this._createIcons()),"disabled"===e&&(this.element.toggleClass("ui-state-disabled",!!t).attr("aria-disabled",t),this.headers.add(this.headers.next()).toggleClass("ui-state-disabled",!!t)),void 0)},_keydown:function(t){if(!t.altKey&&!t.ctrlKey){var i=e.ui.keyCode,s=this.headers.length,n=this.headers.index(t.target),a=!1;switch(t.keyCode){case i.RIGHT:case i.DOWN:a=this.headers[(n+1)%s];break;case i.LEFT:case i.UP:a=this.headers[(n-1+s)%s];break;case i.SPACE:case i.ENTER:this._eventHandler(t);break;case i.HOME:a=this.headers[0];break;case i.END:a=this.headers[s-1]}a&&(e(t.target).attr("tabIndex",-1),e(a).attr("tabIndex",0),a.focus(),t.preventDefault())}},_panelKeyDown:function(t){t.keyCode===e.ui.keyCode.UP&&t.ctrlKey&&e(t.currentTarget).prev().focus()},refresh:function(){var t=this.options;this._processPanels(),t.active===!1&&t.collapsible===!0||!this.headers.length?(t.active=!1,this.active=e()):t.active===!1?this._activate(0):this.active.length&&!e.contains(this.element[0],this.active[0])?this.headers.length===this.headers.find(".ui-state-disabled").length?(t.active=!1,this.active=e()):this._activate(Math.max(0,t.active-1)):t.active=this.headers.index(this.active),this._destroyIcons(),this._refresh()},_processPanels:function(){var e=this.headers,t=this.panels;this.headers=this.element.find(this.options.header).addClass("ui-accordion-header ui-state-default ui-corner-all"),this.panels=this.headers.next().addClass("ui-accordion-content ui-helper-reset ui-widget-content ui-corner-bottom").filter(":not(.ui-accordion-content-active)").hide(),t&&(this._off(e.not(this.headers)),this._off(t.not(this.panels)))},_refresh:function(){var t,i=this.options,s=i.heightStyle,n=this.element.parent();this.active=this._findActive(i.active).addClass("ui-accordion-header-active ui-state-active ui-corner-top").removeClass("ui-corner-all"),this.active.next().addClass("ui-accordion-content-active").show(),this.headers.attr("role","tab").each(function(){var t=e(this),i=t.uniqueId().attr("id"),s=t.next(),n=s.uniqueId().attr("id");t.attr("aria-controls",n),s.attr("aria-labelledby",i)}).next().attr("role","tabpanel"),this.headers.not(this.active).attr({"aria-selected":"false","aria-expanded":"false",tabIndex:-1}).next().attr({"aria-hidden":"true"}).hide(),this.active.length?this.active.attr({"aria-selected":"true","aria-expanded":"true",tabIndex:0}).next().attr({"aria-hidden":"false"}):this.headers.eq(0).attr("tabIndex",0),this._createIcons(),this._setupEvents(i.event),"fill"===s?(t=n.height(),this.element.siblings(":visible").each(function(){var i=e(this),s=i.css("position");"absolute"!==s&&"fixed"!==s&&(t-=i.outerHeight(!0))}),this.headers.each(function(){t-=e(this).outerHeight(!0)}),this.headers.next().each(function(){e(this).height(Math.max(0,t-e(this).innerHeight()+e(this).height()))}).css("overflow","auto")):"auto"===s&&(t=0,this.headers.next().each(function(){t=Math.max(t,e(this).css("height","").height())}).height(t))},_activate:function(t){var i=this._findActive(t)[0];i!==this.active[0]&&(i=i||this.active[0],this._eventHandler({target:i,currentTarget:i,preventDefault:e.noop}))},_findActive:function(t){return"number"==typeof t?this.headers.eq(t):e()},_setupEvents:function(t){var i={keydown:"_keydown"};t&&e.each(t.split(" "),function(e,t){i[t]="_eventHandler"}),this._off(this.headers.add(this.headers.next())),this._on(this.headers,i),this._on(this.headers.next(),{keydown:"_panelKeyDown"}),this._hoverable(this.headers),this._focusable(this.headers)},_eventHandler:function(t){var i=this.options,s=this.active,n=e(t.currentTarget),a=n[0]===s[0],o=a&&i.collapsible,r=o?e():n.next(),h=s.next(),l={oldHeader:s,oldPanel:h,newHeader:o?e():n,newPanel:r};
t.preventDefault(),a&&!i.collapsible||this._trigger("beforeActivate",t,l)===!1||(i.active=o?!1:this.headers.index(n),this.active=a?e():n,this._toggle(l),s.removeClass("ui-accordion-header-active ui-state-active"),i.icons&&s.children(".ui-accordion-header-icon").removeClass(i.icons.activeHeader).addClass(i.icons.header),a||(n.removeClass("ui-corner-all").addClass("ui-accordion-header-active ui-state-active ui-corner-top"),i.icons&&n.children(".ui-accordion-header-icon").removeClass(i.icons.header).addClass(i.icons.activeHeader),n.next().addClass("ui-accordion-content-active")))},_toggle:function(t){var i=t.newPanel,s=this.prevShow.length?this.prevShow:t.oldPanel;this.prevShow.add(this.prevHide).stop(!0,!0),this.prevShow=i,this.prevHide=s,this.options.animate?this._animate(i,s,t):(s.hide(),i.show(),this._toggleComplete(t)),s.attr({"aria-hidden":"true"}),s.prev().attr({"aria-selected":"false","aria-expanded":"false"}),i.length&&s.length?s.prev().attr({tabIndex:-1,"aria-expanded":"false"}):i.length&&this.headers.filter(function(){return 0===parseInt(e(this).attr("tabIndex"),10)}).attr("tabIndex",-1),i.attr("aria-hidden","false").prev().attr({"aria-selected":"true","aria-expanded":"true",tabIndex:0})},_animate:function(e,t,i){var s,n,a,o=this,r=0,h=e.css("box-sizing"),l=e.length&&(!t.length||e.index()<t.index()),u=this.options.animate||{},d=l&&u.down||u,c=function(){o._toggleComplete(i)};return"number"==typeof d&&(a=d),"string"==typeof d&&(n=d),n=n||d.easing||u.easing,a=a||d.duration||u.duration,t.length?e.length?(s=e.show().outerHeight(),t.animate(this.hideProps,{duration:a,easing:n,step:function(e,t){t.now=Math.round(e)}}),e.hide().animate(this.showProps,{duration:a,easing:n,complete:c,step:function(e,i){i.now=Math.round(e),"height"!==i.prop?"content-box"===h&&(r+=i.now):"content"!==o.options.heightStyle&&(i.now=Math.round(s-t.outerHeight()-r),r=0)}}),void 0):t.animate(this.hideProps,a,n,c):e.animate(this.showProps,a,n,c)},_toggleComplete:function(e){var t=e.oldPanel;t.removeClass("ui-accordion-content-active").prev().removeClass("ui-corner-top").addClass("ui-corner-all"),t.length&&(t.parent()[0].className=t.parent()[0].className),this._trigger("activate",null,e)}}),e.widget("ui.menu",{version:"1.11.4",defaultElement:"<ul>",delay:300,options:{icons:{submenu:"ui-icon-carat-1-e"},items:"> *",menus:"ul",position:{my:"left-1 top",at:"right top"},role:"menu",blur:null,focus:null,select:null},_create:function(){this.activeMenu=this.element,this.mouseHandled=!1,this.element.uniqueId().addClass("ui-menu ui-widget ui-widget-content").toggleClass("ui-menu-icons",!!this.element.find(".ui-icon").length).attr({role:this.options.role,tabIndex:0}),this.options.disabled&&this.element.addClass("ui-state-disabled").attr("aria-disabled","true"),this._on({"mousedown .ui-menu-item":function(e){e.preventDefault()},"click .ui-menu-item":function(t){var i=e(t.target);!this.mouseHandled&&i.not(".ui-state-disabled").length&&(this.select(t),t.isPropagationStopped()||(this.mouseHandled=!0),i.has(".ui-menu").length?this.expand(t):!this.element.is(":focus")&&e(this.document[0].activeElement).closest(".ui-menu").length&&(this.element.trigger("focus",[!0]),this.active&&1===this.active.parents(".ui-menu").length&&clearTimeout(this.timer)))},"mouseenter .ui-menu-item":function(t){if(!this.previousFilter){var i=e(t.currentTarget);i.siblings(".ui-state-active").removeClass("ui-state-active"),this.focus(t,i)}},mouseleave:"collapseAll","mouseleave .ui-menu":"collapseAll",focus:function(e,t){var i=this.active||this.element.find(this.options.items).eq(0);t||this.focus(e,i)},blur:function(t){this._delay(function(){e.contains(this.element[0],this.document[0].activeElement)||this.collapseAll(t)})},keydown:"_keydown"}),this.refresh(),this._on(this.document,{click:function(e){this._closeOnDocumentClick(e)&&this.collapseAll(e),this.mouseHandled=!1}})},_destroy:function(){this.element.removeAttr("aria-activedescendant").find(".ui-menu").addBack().removeClass("ui-menu ui-widget ui-widget-content ui-menu-icons ui-front").removeAttr("role").removeAttr("tabIndex").removeAttr("aria-labelledby").removeAttr("aria-expanded").removeAttr("aria-hidden").removeAttr("aria-disabled").removeUniqueId().show(),this.element.find(".ui-menu-item").removeClass("ui-menu-item").removeAttr("role").removeAttr("aria-disabled").removeUniqueId().removeClass("ui-state-hover").removeAttr("tabIndex").removeAttr("role").removeAttr("aria-haspopup").children().each(function(){var t=e(this);t.data("ui-menu-submenu-carat")&&t.remove()}),this.element.find(".ui-menu-divider").removeClass("ui-menu-divider ui-widget-content")},_keydown:function(t){var i,s,n,a,o=!0;switch(t.keyCode){case e.ui.keyCode.PAGE_UP:this.previousPage(t);break;case e.ui.keyCode.PAGE_DOWN:this.nextPage(t);break;case e.ui.keyCode.HOME:this._move("first","first",t);break;case e.ui.keyCode.END:this._move("last","last",t);break;case e.ui.keyCode.UP:this.previous(t);break;case e.ui.keyCode.DOWN:this.next(t);break;case e.ui.keyCode.LEFT:this.collapse(t);break;case e.ui.keyCode.RIGHT:this.active&&!this.active.is(".ui-state-disabled")&&this.expand(t);break;case e.ui.keyCode.ENTER:case e.ui.keyCode.SPACE:this._activate(t);break;case e.ui.keyCode.ESCAPE:this.collapse(t);break;default:o=!1,s=this.previousFilter||"",n=String.fromCharCode(t.keyCode),a=!1,clearTimeout(this.filterTimer),n===s?a=!0:n=s+n,i=this._filterMenuItems(n),i=a&&-1!==i.index(this.active.next())?this.active.nextAll(".ui-menu-item"):i,i.length||(n=String.fromCharCode(t.keyCode),i=this._filterMenuItems(n)),i.length?(this.focus(t,i),this.previousFilter=n,this.filterTimer=this._delay(function(){delete this.previousFilter},1e3)):delete this.previousFilter}o&&t.preventDefault()},_activate:function(e){this.active.is(".ui-state-disabled")||(this.active.is("[aria-haspopup='true']")?this.expand(e):this.select(e))},refresh:function(){var t,i,s=this,n=this.options.icons.submenu,a=this.element.find(this.options.menus);this.element.toggleClass("ui-menu-icons",!!this.element.find(".ui-icon").length),a.filter(":not(.ui-menu)").addClass("ui-menu ui-widget ui-widget-content ui-front").hide().attr({role:this.options.role,"aria-hidden":"true","aria-expanded":"false"}).each(function(){var t=e(this),i=t.parent(),s=e("<span>").addClass("ui-menu-icon ui-icon "+n).data("ui-menu-submenu-carat",!0);i.attr("aria-haspopup","true").prepend(s),t.attr("aria-labelledby",i.attr("id"))}),t=a.add(this.element),i=t.find(this.options.items),i.not(".ui-menu-item").each(function(){var t=e(this);s._isDivider(t)&&t.addClass("ui-widget-content ui-menu-divider")}),i.not(".ui-menu-item, .ui-menu-divider").addClass("ui-menu-item").uniqueId().attr({tabIndex:-1,role:this._itemRole()}),i.filter(".ui-state-disabled").attr("aria-disabled","true"),this.active&&!e.contains(this.element[0],this.active[0])&&this.blur()},_itemRole:function(){return{menu:"menuitem",listbox:"option"}[this.options.role]},_setOption:function(e,t){"icons"===e&&this.element.find(".ui-menu-icon").removeClass(this.options.icons.submenu).addClass(t.submenu),"disabled"===e&&this.element.toggleClass("ui-state-disabled",!!t).attr("aria-disabled",t),this._super(e,t)},focus:function(e,t){var i,s;this.blur(e,e&&"focus"===e.type),this._scrollIntoView(t),this.active=t.first(),s=this.active.addClass("ui-state-focus").removeClass("ui-state-active"),this.options.role&&this.element.attr("aria-activedescendant",s.attr("id")),this.active.parent().closest(".ui-menu-item").addClass("ui-state-active"),e&&"keydown"===e.type?this._close():this.timer=this._delay(function(){this._close()},this.delay),i=t.children(".ui-menu"),i.length&&e&&/^mouse/.test(e.type)&&this._startOpening(i),this.activeMenu=t.parent(),this._trigger("focus",e,{item:t})},_scrollIntoView:function(t){var i,s,n,a,o,r;this._hasScroll()&&(i=parseFloat(e.css(this.activeMenu[0],"borderTopWidth"))||0,s=parseFloat(e.css(this.activeMenu[0],"paddingTop"))||0,n=t.offset().top-this.activeMenu.offset().top-i-s,a=this.activeMenu.scrollTop(),o=this.activeMenu.height(),r=t.outerHeight(),0>n?this.activeMenu.scrollTop(a+n):n+r>o&&this.activeMenu.scrollTop(a+n-o+r))},blur:function(e,t){t||clearTimeout(this.timer),this.active&&(this.active.removeClass("ui-state-focus"),this.active=null,this._trigger("blur",e,{item:this.active}))},_startOpening:function(e){clearTimeout(this.timer),"true"===e.attr("aria-hidden")&&(this.timer=this._delay(function(){this._close(),this._open(e)},this.delay))},_open:function(t){var i=e.extend({of:this.active},this.options.position);clearTimeout(this.timer),this.element.find(".ui-menu").not(t.parents(".ui-menu")).hide().attr("aria-hidden","true"),t.show().removeAttr("aria-hidden").attr("aria-expanded","true").position(i)},collapseAll:function(t,i){clearTimeout(this.timer),this.timer=this._delay(function(){var s=i?this.element:e(t&&t.target).closest(this.element.find(".ui-menu"));s.length||(s=this.element),this._close(s),this.blur(t),this.activeMenu=s},this.delay)},_close:function(e){e||(e=this.active?this.active.parent():this.element),e.find(".ui-menu").hide().attr("aria-hidden","true").attr("aria-expanded","false").end().find(".ui-state-active").not(".ui-state-focus").removeClass("ui-state-active")},_closeOnDocumentClick:function(t){return!e(t.target).closest(".ui-menu").length},_isDivider:function(e){return!/[^\-\u2014\u2013\s]/.test(e.text())},collapse:function(e){var t=this.active&&this.active.parent().closest(".ui-menu-item",this.element);t&&t.length&&(this._close(),this.focus(e,t))},expand:function(e){var t=this.active&&this.active.children(".ui-menu ").find(this.options.items).first();t&&t.length&&(this._open(t.parent()),this._delay(function(){this.focus(e,t)}))},next:function(e){this._move("next","first",e)},previous:function(e){this._move("prev","last",e)},isFirstItem:function(){return this.active&&!this.active.prevAll(".ui-menu-item").length},isLastItem:function(){return this.active&&!this.active.nextAll(".ui-menu-item").length},_move:function(e,t,i){var s;this.active&&(s="first"===e||"last"===e?this.active["first"===e?"prevAll":"nextAll"](".ui-menu-item").eq(-1):this.active[e+"All"](".ui-menu-item").eq(0)),s&&s.length&&this.active||(s=this.activeMenu.find(this.options.items)[t]()),this.focus(i,s)},nextPage:function(t){var i,s,n;return this.active?(this.isLastItem()||(this._hasScroll()?(s=this.active.offset().top,n=this.element.height(),this.active.nextAll(".ui-menu-item").each(function(){return i=e(this),0>i.offset().top-s-n}),this.focus(t,i)):this.focus(t,this.activeMenu.find(this.options.items)[this.active?"last":"first"]())),void 0):(this.next(t),void 0)},previousPage:function(t){var i,s,n;return this.active?(this.isFirstItem()||(this._hasScroll()?(s=this.active.offset().top,n=this.element.height(),this.active.prevAll(".ui-menu-item").each(function(){return i=e(this),i.offset().top-s+n>0}),this.focus(t,i)):this.focus(t,this.activeMenu.find(this.options.items).first())),void 0):(this.next(t),void 0)},_hasScroll:function(){return this.element.outerHeight()<this.element.prop("scrollHeight")},select:function(t){this.active=this.active||e(t.target).closest(".ui-menu-item");var i={item:this.active};this.active.has(".ui-menu").length||this.collapseAll(t,!0),this._trigger("select",t,i)},_filterMenuItems:function(t){var i=t.replace(/[\-\[\]{}()*+?.,\\\^$|#\s]/g,"\\$&"),s=RegExp("^"+i,"i");return this.activeMenu.find(this.options.items).filter(".ui-menu-item").filter(function(){return s.test(e.trim(e(this).text()))})}}),e.widget("ui.autocomplete",{version:"1.11.4",defaultElement:"<input>",options:{appendTo:null,autoFocus:!1,delay:300,minLength:1,position:{my:"left top",at:"left bottom",collision:"none"},source:null,change:null,close:null,focus:null,open:null,response:null,search:null,select:null},requestIndex:0,pending:0,_create:function(){var t,i,s,n=this.element[0].nodeName.toLowerCase(),a="textarea"===n,o="input"===n;this.isMultiLine=a?!0:o?!1:this.element.prop("isContentEditable"),this.valueMethod=this.element[a||o?"val":"text"],this.isNewMenu=!0,this.element.addClass("ui-autocomplete-input").attr("autocomplete","off"),this._on(this.element,{keydown:function(n){if(this.element.prop("readOnly"))return t=!0,s=!0,i=!0,void 0;t=!1,s=!1,i=!1;var a=e.ui.keyCode;switch(n.keyCode){case a.PAGE_UP:t=!0,this._move("previousPage",n);break;case a.PAGE_DOWN:t=!0,this._move("nextPage",n);break;case a.UP:t=!0,this._keyEvent("previous",n);break;case a.DOWN:t=!0,this._keyEvent("next",n);break;case a.ENTER:this.menu.active&&(t=!0,n.preventDefault(),this.menu.select(n));break;case a.TAB:this.menu.active&&this.menu.select(n);break;case a.ESCAPE:this.menu.element.is(":visible")&&(this.isMultiLine||this._value(this.term),this.close(n),n.preventDefault());break;default:i=!0,this._searchTimeout(n)}},keypress:function(s){if(t)return t=!1,(!this.isMultiLine||this.menu.element.is(":visible"))&&s.preventDefault(),void 0;if(!i){var n=e.ui.keyCode;switch(s.keyCode){case n.PAGE_UP:this._move("previousPage",s);break;case n.PAGE_DOWN:this._move("nextPage",s);break;case n.UP:this._keyEvent("previous",s);break;case n.DOWN:this._keyEvent("next",s)}}},input:function(e){return s?(s=!1,e.preventDefault(),void 0):(this._searchTimeout(e),void 0)},focus:function(){this.selectedItem=null,this.previous=this._value()},blur:function(e){return this.cancelBlur?(delete this.cancelBlur,void 0):(clearTimeout(this.searching),this.close(e),this._change(e),void 0)}}),this._initSource(),this.menu=e("<ul>").addClass("ui-autocomplete ui-front").appendTo(this._appendTo()).menu({role:null}).hide().menu("instance"),this._on(this.menu.element,{mousedown:function(t){t.preventDefault(),this.cancelBlur=!0,this._delay(function(){delete this.cancelBlur});var i=this.menu.element[0];e(t.target).closest(".ui-menu-item").length||this._delay(function(){var t=this;this.document.one("mousedown",function(s){s.target===t.element[0]||s.target===i||e.contains(i,s.target)||t.close()})})},menufocus:function(t,i){var s,n;return this.isNewMenu&&(this.isNewMenu=!1,t.originalEvent&&/^mouse/.test(t.originalEvent.type))?(this.menu.blur(),this.document.one("mousemove",function(){e(t.target).trigger(t.originalEvent)}),void 0):(n=i.item.data("ui-autocomplete-item"),!1!==this._trigger("focus",t,{item:n})&&t.originalEvent&&/^key/.test(t.originalEvent.type)&&this._value(n.value),s=i.item.attr("aria-label")||n.value,s&&e.trim(s).length&&(this.liveRegion.children().hide(),e("<div>").text(s).appendTo(this.liveRegion)),void 0)},menuselect:function(e,t){var i=t.item.data("ui-autocomplete-item"),s=this.previous;this.element[0]!==this.document[0].activeElement&&(this.element.focus(),this.previous=s,this._delay(function(){this.previous=s,this.selectedItem=i})),!1!==this._trigger("select",e,{item:i})&&this._value(i.value),this.term=this._value(),this.close(e),this.selectedItem=i}}),this.liveRegion=e("<span>",{role:"status","aria-live":"assertive","aria-relevant":"additions"}).addClass("ui-helper-hidden-accessible").appendTo(this.document[0].body),this._on(this.window,{beforeunload:function(){this.element.removeAttr("autocomplete")}})},_destroy:function(){clearTimeout(this.searching),this.element.removeClass("ui-autocomplete-input").removeAttr("autocomplete"),this.menu.element.remove(),this.liveRegion.remove()},_setOption:function(e,t){this._super(e,t),"source"===e&&this._initSource(),"appendTo"===e&&this.menu.element.appendTo(this._appendTo()),"disabled"===e&&t&&this.xhr&&this.xhr.abort()},_appendTo:function(){var t=this.options.appendTo;return t&&(t=t.jquery||t.nodeType?e(t):this.document.find(t).eq(0)),t&&t[0]||(t=this.element.closest(".ui-front")),t.length||(t=this.document[0].body),t},_initSource:function(){var t,i,s=this;e.isArray(this.options.source)?(t=this.options.source,this.source=function(i,s){s(e.ui.autocomplete.filter(t,i.term))}):"string"==typeof this.options.source?(i=this.options.source,this.source=function(t,n){s.xhr&&s.xhr.abort(),s.xhr=e.ajax({url:i,data:t,dataType:"json",success:function(e){n(e)},error:function(){n([])}})}):this.source=this.options.source},_searchTimeout:function(e){clearTimeout(this.searching),this.searching=this._delay(function(){var t=this.term===this._value(),i=this.menu.element.is(":visible"),s=e.altKey||e.ctrlKey||e.metaKey||e.shiftKey;(!t||t&&!i&&!s)&&(this.selectedItem=null,this.search(null,e))},this.options.delay)},search:function(e,t){return e=null!=e?e:this._value(),this.term=this._value(),e.length<this.options.minLength?this.close(t):this._trigger("search",t)!==!1?this._search(e):void 0},_search:function(e){this.pending++,this.element.addClass("ui-autocomplete-loading"),this.cancelSearch=!1,this.source({term:e},this._response())},_response:function(){var t=++this.requestIndex;return e.proxy(function(e){t===this.requestIndex&&this.__response(e),this.pending--,this.pending||this.element.removeClass("ui-autocomplete-loading")},this)},__response:function(e){e&&(e=this._normalize(e)),this._trigger("response",null,{content:e}),!this.options.disabled&&e&&e.length&&!this.cancelSearch?(this._suggest(e),this._trigger("open")):this._close()},close:function(e){this.cancelSearch=!0,this._close(e)},_close:function(e){this.menu.element.is(":visible")&&(this.menu.element.hide(),this.menu.blur(),this.isNewMenu=!0,this._trigger("close",e))},_change:function(e){this.previous!==this._value()&&this._trigger("change",e,{item:this.selectedItem})},_normalize:function(t){return t.length&&t[0].label&&t[0].value?t:e.map(t,function(t){return"string"==typeof t?{label:t,value:t}:e.extend({},t,{label:t.label||t.value,value:t.value||t.label})})},_suggest:function(t){var i=this.menu.element.empty();this._renderMenu(i,t),this.isNewMenu=!0,this.menu.refresh(),i.show(),this._resizeMenu(),i.position(e.extend({of:this.element},this.options.position)),this.options.autoFocus&&this.menu.next()},_resizeMenu:function(){var e=this.menu.element;e.outerWidth(Math.max(e.width("").outerWidth()+1,this.element.outerWidth()))},_renderMenu:function(t,i){var s=this;e.each(i,function(e,i){s._renderItemData(t,i)})},_renderItemData:function(e,t){return this._renderItem(e,t).data("ui-autocomplete-item",t)},_renderItem:function(t,i){return e("<li>").text(i.label).appendTo(t)},_move:function(e,t){return this.menu.element.is(":visible")?this.menu.isFirstItem()&&/^previous/.test(e)||this.menu.isLastItem()&&/^next/.test(e)?(this.isMultiLine||this._value(this.term),this.menu.blur(),void 0):(this.menu[e](t),void 0):(this.search(null,t),void 0)},widget:function(){return this.menu.element},_value:function(){return this.valueMethod.apply(this.element,arguments)},_keyEvent:function(e,t){(!this.isMultiLine||this.menu.element.is(":visible"))&&(this._move(e,t),t.preventDefault())}}),e.extend(e.ui.autocomplete,{escapeRegex:function(e){return e.replace(/[\-\[\]{}()*+?.,\\\^$|#\s]/g,"\\$&")},filter:function(t,i){var s=RegExp(e.ui.autocomplete.escapeRegex(i),"i");return e.grep(t,function(e){return s.test(e.label||e.value||e)})}}),e.widget("ui.autocomplete",e.ui.autocomplete,{options:{messages:{noResults:"No search results.",results:function(e){return e+(e>1?" results are":" result is")+" available, use up and down arrow keys to navigate."}}},__response:function(t){var i;this._superApply(arguments),this.options.disabled||this.cancelSearch||(i=t&&t.length?this.options.messages.results(t.length):this.options.messages.noResults,this.liveRegion.children().hide(),e("<div>").text(i).appendTo(this.liveRegion))}}),e.ui.autocomplete;var r,h="ui-button ui-widget ui-state-default ui-corner-all",l="ui-button-icons-only ui-button-icon-only ui-button-text-icons ui-button-text-icon-primary ui-button-text-icon-secondary ui-button-text-only",u=function(){var t=e(this);setTimeout(function(){t.find(":ui-button").button("refresh")},1)},d=function(t){var i=t.name,s=t.form,n=e([]);return i&&(i=i.replace(/'/g,"\\'"),n=s?e(s).find("[name='"+i+"'][type=radio]"):e("[name='"+i+"'][type=radio]",t.ownerDocument).filter(function(){return!this.form})),n};e.widget("ui.button",{version:"1.11.4",defaultElement:"<button>",options:{disabled:null,text:!0,label:null,icons:{primary:null,secondary:null}},_create:function(){this.element.closest("form").unbind("reset"+this.eventNamespace).bind("reset"+this.eventNamespace,u),"boolean"!=typeof this.options.disabled?this.options.disabled=!!this.element.prop("disabled"):this.element.prop("disabled",this.options.disabled),this._determineButtonType(),this.hasTitle=!!this.buttonElement.attr("title");var t=this,i=this.options,s="checkbox"===this.type||"radio"===this.type,n=s?"":"ui-state-active";null===i.label&&(i.label="input"===this.type?this.buttonElement.val():this.buttonElement.html()),this._hoverable(this.buttonElement),this.buttonElement.addClass(h).attr("role","button").bind("mouseenter"+this.eventNamespace,function(){i.disabled||this===r&&e(this).addClass("ui-state-active")}).bind("mouseleave"+this.eventNamespace,function(){i.disabled||e(this).removeClass(n)}).bind("click"+this.eventNamespace,function(e){i.disabled&&(e.preventDefault(),e.stopImmediatePropagation())}),this._on({focus:function(){this.buttonElement.addClass("ui-state-focus")},blur:function(){this.buttonElement.removeClass("ui-state-focus")}}),s&&this.element.bind("change"+this.eventNamespace,function(){t.refresh()}),"checkbox"===this.type?this.buttonElement.bind("click"+this.eventNamespace,function(){return i.disabled?!1:void 0}):"radio"===this.type?this.buttonElement.bind("click"+this.eventNamespace,function(){if(i.disabled)return!1;e(this).addClass("ui-state-active"),t.buttonElement.attr("aria-pressed","true");var s=t.element[0];d(s).not(s).map(function(){return e(this).button("widget")[0]}).removeClass("ui-state-active").attr("aria-pressed","false")}):(this.buttonElement.bind("mousedown"+this.eventNamespace,function(){return i.disabled?!1:(e(this).addClass("ui-state-active"),r=this,t.document.one("mouseup",function(){r=null}),void 0)}).bind("mouseup"+this.eventNamespace,function(){return i.disabled?!1:(e(this).removeClass("ui-state-active"),void 0)}).bind("keydown"+this.eventNamespace,function(t){return i.disabled?!1:((t.keyCode===e.ui.keyCode.SPACE||t.keyCode===e.ui.keyCode.ENTER)&&e(this).addClass("ui-state-active"),void 0)}).bind("keyup"+this.eventNamespace+" blur"+this.eventNamespace,function(){e(this).removeClass("ui-state-active")}),this.buttonElement.is("a")&&this.buttonElement.keyup(function(t){t.keyCode===e.ui.keyCode.SPACE&&e(this).click()})),this._setOption("disabled",i.disabled),this._resetButton()},_determineButtonType:function(){var e,t,i;this.type=this.element.is("[type=checkbox]")?"checkbox":this.element.is("[type=radio]")?"radio":this.element.is("input")?"input":"button","checkbox"===this.type||"radio"===this.type?(e=this.element.parents().last(),t="label[for='"+this.element.attr("id")+"']",this.buttonElement=e.find(t),this.buttonElement.length||(e=e.length?e.siblings():this.element.siblings(),this.buttonElement=e.filter(t),this.buttonElement.length||(this.buttonElement=e.find(t))),this.element.addClass("ui-helper-hidden-accessible"),i=this.element.is(":checked"),i&&this.buttonElement.addClass("ui-state-active"),this.buttonElement.prop("aria-pressed",i)):this.buttonElement=this.element},widget:function(){return this.buttonElement},_destroy:function(){this.element.removeClass("ui-helper-hidden-accessible"),this.buttonElement.removeClass(h+" ui-state-active "+l).removeAttr("role").removeAttr("aria-pressed").html(this.buttonElement.find(".ui-button-text").html()),this.hasTitle||this.buttonElement.removeAttr("title")},_setOption:function(e,t){return this._super(e,t),"disabled"===e?(this.widget().toggleClass("ui-state-disabled",!!t),this.element.prop("disabled",!!t),t&&("checkbox"===this.type||"radio"===this.type?this.buttonElement.removeClass("ui-state-focus"):this.buttonElement.removeClass("ui-state-focus ui-state-active")),void 0):(this._resetButton(),void 0)},refresh:function(){var t=this.element.is("input, button")?this.element.is(":disabled"):this.element.hasClass("ui-button-disabled");t!==this.options.disabled&&this._setOption("disabled",t),"radio"===this.type?d(this.element[0]).each(function(){e(this).is(":checked")?e(this).button("widget").addClass("ui-state-active").attr("aria-pressed","true"):e(this).button("widget").removeClass("ui-state-active").attr("aria-pressed","false")}):"checkbox"===this.type&&(this.element.is(":checked")?this.buttonElement.addClass("ui-state-active").attr("aria-pressed","true"):this.buttonElement.removeClass("ui-state-active").attr("aria-pressed","false"))},_resetButton:function(){if("input"===this.type)return this.options.label&&this.element.val(this.options.label),void 0;var t=this.buttonElement.removeClass(l),i=e("<span></span>",this.document[0]).addClass("ui-button-text").html(this.options.label).appendTo(t.empty()).text(),s=this.options.icons,n=s.primary&&s.secondary,a=[];s.primary||s.secondary?(this.options.text&&a.push("ui-button-text-icon"+(n?"s":s.primary?"-primary":"-secondary")),s.primary&&t.prepend("<span class='ui-button-icon-primary ui-icon "+s.primary+"'></span>"),s.secondary&&t.append("<span class='ui-button-icon-secondary ui-icon "+s.secondary+"'></span>"),this.options.text||(a.push(n?"ui-button-icons-only":"ui-button-icon-only"),this.hasTitle||t.attr("title",e.trim(i)))):a.push("ui-button-text-only"),t.addClass(a.join(" "))}}),e.widget("ui.buttonset",{version:"1.11.4",options:{items:"button, input[type=button], input[type=submit], input[type=reset], input[type=checkbox], input[type=radio], a, :data(ui-button)"},_create:function(){this.element.addClass("ui-buttonset")},_init:function(){this.refresh()},_setOption:function(e,t){"disabled"===e&&this.buttons.button("option",e,t),this._super(e,t)},refresh:function(){var t="rtl"===this.element.css("direction"),i=this.element.find(this.options.items),s=i.filter(":ui-button");i.not(":ui-button").button(),s.button("refresh"),this.buttons=i.map(function(){return e(this).button("widget")[0]}).removeClass("ui-corner-all ui-corner-left ui-corner-right").filter(":first").addClass(t?"ui-corner-right":"ui-corner-left").end().filter(":last").addClass(t?"ui-corner-left":"ui-corner-right").end().end()},_destroy:function(){this.element.removeClass("ui-buttonset"),this.buttons.map(function(){return e(this).button("widget")[0]}).removeClass("ui-corner-left ui-corner-right").end().button("destroy")}}),e.ui.button,e.widget("ui.dialog",{version:"1.11.4",options:{appendTo:"body",autoOpen:!0,buttons:[],closeOnEscape:!0,closeText:"Close",dialogClass:"",draggable:!0,hide:null,height:"auto",maxHeight:null,maxWidth:null,minHeight:150,minWidth:150,modal:!1,position:{my:"center",at:"center",of:window,collision:"fit",using:function(t){var i=e(this).css(t).offset().top;0>i&&e(this).css("top",t.top-i)}},resizable:!0,show:null,title:null,width:300,beforeClose:null,close:null,drag:null,dragStart:null,dragStop:null,focus:null,open:null,resize:null,resizeStart:null,resizeStop:null},sizeRelatedOptions:{buttons:!0,height:!0,maxHeight:!0,maxWidth:!0,minHeight:!0,minWidth:!0,width:!0},resizableRelatedOptions:{maxHeight:!0,maxWidth:!0,minHeight:!0,minWidth:!0},_create:function(){this.originalCss={display:this.element[0].style.display,width:this.element[0].style.width,minHeight:this.element[0].style.minHeight,maxHeight:this.element[0].style.maxHeight,height:this.element[0].style.height},this.originalPosition={parent:this.element.parent(),index:this.element.parent().children().index(this.element)},this.originalTitle=this.element.attr("title"),this.options.title=this.options.title||this.originalTitle,this._createWrapper(),this.element.show().removeAttr("title").addClass("ui-dialog-content ui-widget-content").appendTo(this.uiDialog),this._createTitlebar(),this._createButtonPane(),this.options.draggable&&e.fn.draggable&&this._makeDraggable(),this.options.resizable&&e.fn.resizable&&this._makeResizable(),this._isOpen=!1,this._trackFocus()},_init:function(){this.options.autoOpen&&this.open()},_appendTo:function(){var t=this.options.appendTo;return t&&(t.jquery||t.nodeType)?e(t):this.document.find(t||"body").eq(0)},_destroy:function(){var e,t=this.originalPosition;this._untrackInstance(),this._destroyOverlay(),this.element.removeUniqueId().removeClass("ui-dialog-content ui-widget-content").css(this.originalCss).detach(),this.uiDialog.stop(!0,!0).remove(),this.originalTitle&&this.element.attr("title",this.originalTitle),e=t.parent.children().eq(t.index),e.length&&e[0]!==this.element[0]?e.before(this.element):t.parent.append(this.element)},widget:function(){return this.uiDialog},disable:e.noop,enable:e.noop,close:function(t){var i,s=this;if(this._isOpen&&this._trigger("beforeClose",t)!==!1){if(this._isOpen=!1,this._focusedElement=null,this._destroyOverlay(),this._untrackInstance(),!this.opener.filter(":focusable").focus().length)try{i=this.document[0].activeElement,i&&"body"!==i.nodeName.toLowerCase()&&e(i).blur()}catch(n){}this._hide(this.uiDialog,this.options.hide,function(){s._trigger("close",t)})}},isOpen:function(){return this._isOpen},moveToTop:function(){this._moveToTop()},_moveToTop:function(t,i){var s=!1,n=this.uiDialog.siblings(".ui-front:visible").map(function(){return+e(this).css("z-index")}).get(),a=Math.max.apply(null,n);return a>=+this.uiDialog.css("z-index")&&(this.uiDialog.css("z-index",a+1),s=!0),s&&!i&&this._trigger("focus",t),s},open:function(){var t=this;return this._isOpen?(this._moveToTop()&&this._focusTabbable(),void 0):(this._isOpen=!0,this.opener=e(this.document[0].activeElement),this._size(),this._position(),this._createOverlay(),this._moveToTop(null,!0),this.overlay&&this.overlay.css("z-index",this.uiDialog.css("z-index")-1),this._show(this.uiDialog,this.options.show,function(){t._focusTabbable(),t._trigger("focus")}),this._makeFocusTarget(),this._trigger("open"),void 0)},_focusTabbable:function(){var e=this._focusedElement;e||(e=this.element.find("[autofocus]")),e.length||(e=this.element.find(":tabbable")),e.length||(e=this.uiDialogButtonPane.find(":tabbable")),e.length||(e=this.uiDialogTitlebarClose.filter(":tabbable")),e.length||(e=this.uiDialog),e.eq(0).focus()},_keepFocus:function(t){function i(){var t=this.document[0].activeElement,i=this.uiDialog[0]===t||e.contains(this.uiDialog[0],t);i||this._focusTabbable()}t.preventDefault(),i.call(this),this._delay(i)},_createWrapper:function(){this.uiDialog=e("<div>").addClass("ui-dialog ui-widget ui-widget-content ui-corner-all ui-front "+this.options.dialogClass).hide().attr({tabIndex:-1,role:"dialog"}).appendTo(this._appendTo()),this._on(this.uiDialog,{keydown:function(t){if(this.options.closeOnEscape&&!t.isDefaultPrevented()&&t.keyCode&&t.keyCode===e.ui.keyCode.ESCAPE)return t.preventDefault(),this.close(t),void 0;if(t.keyCode===e.ui.keyCode.TAB&&!t.isDefaultPrevented()){var i=this.uiDialog.find(":tabbable"),s=i.filter(":first"),n=i.filter(":last");t.target!==n[0]&&t.target!==this.uiDialog[0]||t.shiftKey?t.target!==s[0]&&t.target!==this.uiDialog[0]||!t.shiftKey||(this._delay(function(){n.focus()}),t.preventDefault()):(this._delay(function(){s.focus()}),t.preventDefault())}},mousedown:function(e){this._moveToTop(e)&&this._focusTabbable()}}),this.element.find("[aria-describedby]").length||this.uiDialog.attr({"aria-describedby":this.element.uniqueId().attr("id")})},_createTitlebar:function(){var t;this.uiDialogTitlebar=e("<div>").addClass("ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix").prependTo(this.uiDialog),this._on(this.uiDialogTitlebar,{mousedown:function(t){e(t.target).closest(".ui-dialog-titlebar-close")||this.uiDialog.focus()}}),this.uiDialogTitlebarClose=e("<button type='button'></button>").button({label:this.options.closeText,icons:{primary:"ui-icon-closethick"},text:!1}).addClass("ui-dialog-titlebar-close").appendTo(this.uiDialogTitlebar),this._on(this.uiDialogTitlebarClose,{click:function(e){e.preventDefault(),this.close(e)}}),t=e("<span>").uniqueId().addClass("ui-dialog-title").prependTo(this.uiDialogTitlebar),this._title(t),this.uiDialog.attr({"aria-labelledby":t.attr("id")})},_title:function(e){this.options.title||e.html("&#160;"),e.text(this.options.title)
},_createButtonPane:function(){this.uiDialogButtonPane=e("<div>").addClass("ui-dialog-buttonpane ui-widget-content ui-helper-clearfix"),this.uiButtonSet=e("<div>").addClass("ui-dialog-buttonset").appendTo(this.uiDialogButtonPane),this._createButtons()},_createButtons:function(){var t=this,i=this.options.buttons;return this.uiDialogButtonPane.remove(),this.uiButtonSet.empty(),e.isEmptyObject(i)||e.isArray(i)&&!i.length?(this.uiDialog.removeClass("ui-dialog-buttons"),void 0):(e.each(i,function(i,s){var n,a;s=e.isFunction(s)?{click:s,text:i}:s,s=e.extend({type:"button"},s),n=s.click,s.click=function(){n.apply(t.element[0],arguments)},a={icons:s.icons,text:s.showText},delete s.icons,delete s.showText,e("<button></button>",s).button(a).appendTo(t.uiButtonSet)}),this.uiDialog.addClass("ui-dialog-buttons"),this.uiDialogButtonPane.appendTo(this.uiDialog),void 0)},_makeDraggable:function(){function t(e){return{position:e.position,offset:e.offset}}var i=this,s=this.options;this.uiDialog.draggable({cancel:".ui-dialog-content, .ui-dialog-titlebar-close",handle:".ui-dialog-titlebar",containment:"document",start:function(s,n){e(this).addClass("ui-dialog-dragging"),i._blockFrames(),i._trigger("dragStart",s,t(n))},drag:function(e,s){i._trigger("drag",e,t(s))},stop:function(n,a){var o=a.offset.left-i.document.scrollLeft(),r=a.offset.top-i.document.scrollTop();s.position={my:"left top",at:"left"+(o>=0?"+":"")+o+" "+"top"+(r>=0?"+":"")+r,of:i.window},e(this).removeClass("ui-dialog-dragging"),i._unblockFrames(),i._trigger("dragStop",n,t(a))}})},_makeResizable:function(){function t(e){return{originalPosition:e.originalPosition,originalSize:e.originalSize,position:e.position,size:e.size}}var i=this,s=this.options,n=s.resizable,a=this.uiDialog.css("position"),o="string"==typeof n?n:"n,e,s,w,se,sw,ne,nw";this.uiDialog.resizable({cancel:".ui-dialog-content",containment:"document",alsoResize:this.element,maxWidth:s.maxWidth,maxHeight:s.maxHeight,minWidth:s.minWidth,minHeight:this._minHeight(),handles:o,start:function(s,n){e(this).addClass("ui-dialog-resizing"),i._blockFrames(),i._trigger("resizeStart",s,t(n))},resize:function(e,s){i._trigger("resize",e,t(s))},stop:function(n,a){var o=i.uiDialog.offset(),r=o.left-i.document.scrollLeft(),h=o.top-i.document.scrollTop();s.height=i.uiDialog.height(),s.width=i.uiDialog.width(),s.position={my:"left top",at:"left"+(r>=0?"+":"")+r+" "+"top"+(h>=0?"+":"")+h,of:i.window},e(this).removeClass("ui-dialog-resizing"),i._unblockFrames(),i._trigger("resizeStop",n,t(a))}}).css("position",a)},_trackFocus:function(){this._on(this.widget(),{focusin:function(t){this._makeFocusTarget(),this._focusedElement=e(t.target)}})},_makeFocusTarget:function(){this._untrackInstance(),this._trackingInstances().unshift(this)},_untrackInstance:function(){var t=this._trackingInstances(),i=e.inArray(this,t);-1!==i&&t.splice(i,1)},_trackingInstances:function(){var e=this.document.data("ui-dialog-instances");return e||(e=[],this.document.data("ui-dialog-instances",e)),e},_minHeight:function(){var e=this.options;return"auto"===e.height?e.minHeight:Math.min(e.minHeight,e.height)},_position:function(){var e=this.uiDialog.is(":visible");e||this.uiDialog.show(),this.uiDialog.position(this.options.position),e||this.uiDialog.hide()},_setOptions:function(t){var i=this,s=!1,n={};e.each(t,function(e,t){i._setOption(e,t),e in i.sizeRelatedOptions&&(s=!0),e in i.resizableRelatedOptions&&(n[e]=t)}),s&&(this._size(),this._position()),this.uiDialog.is(":data(ui-resizable)")&&this.uiDialog.resizable("option",n)},_setOption:function(e,t){var i,s,n=this.uiDialog;"dialogClass"===e&&n.removeClass(this.options.dialogClass).addClass(t),"disabled"!==e&&(this._super(e,t),"appendTo"===e&&this.uiDialog.appendTo(this._appendTo()),"buttons"===e&&this._createButtons(),"closeText"===e&&this.uiDialogTitlebarClose.button({label:""+t}),"draggable"===e&&(i=n.is(":data(ui-draggable)"),i&&!t&&n.draggable("destroy"),!i&&t&&this._makeDraggable()),"position"===e&&this._position(),"resizable"===e&&(s=n.is(":data(ui-resizable)"),s&&!t&&n.resizable("destroy"),s&&"string"==typeof t&&n.resizable("option","handles",t),s||t===!1||this._makeResizable()),"title"===e&&this._title(this.uiDialogTitlebar.find(".ui-dialog-title")))},_size:function(){var e,t,i,s=this.options;this.element.show().css({width:"auto",minHeight:0,maxHeight:"none",height:0}),s.minWidth>s.width&&(s.width=s.minWidth),e=this.uiDialog.css({height:"auto",width:s.width}).outerHeight(),t=Math.max(0,s.minHeight-e),i="number"==typeof s.maxHeight?Math.max(0,s.maxHeight-e):"none","auto"===s.height?this.element.css({minHeight:t,maxHeight:i,height:"auto"}):this.element.height(Math.max(0,s.height-e)),this.uiDialog.is(":data(ui-resizable)")&&this.uiDialog.resizable("option","minHeight",this._minHeight())},_blockFrames:function(){this.iframeBlocks=this.document.find("iframe").map(function(){var t=e(this);return e("<div>").css({position:"absolute",width:t.outerWidth(),height:t.outerHeight()}).appendTo(t.parent()).offset(t.offset())[0]})},_unblockFrames:function(){this.iframeBlocks&&(this.iframeBlocks.remove(),delete this.iframeBlocks)},_allowInteraction:function(t){return e(t.target).closest(".ui-dialog").length?!0:!!e(t.target).closest(".ui-datepicker").length},_createOverlay:function(){if(this.options.modal){var t=!0;this._delay(function(){t=!1}),this.document.data("ui-dialog-overlays")||this._on(this.document,{focusin:function(e){t||this._allowInteraction(e)||(e.preventDefault(),this._trackingInstances()[0]._focusTabbable())}}),this.overlay=e("<div>").addClass("ui-widget-overlay ui-front").appendTo(this._appendTo()),this._on(this.overlay,{mousedown:"_keepFocus"}),this.document.data("ui-dialog-overlays",(this.document.data("ui-dialog-overlays")||0)+1)}},_destroyOverlay:function(){if(this.options.modal&&this.overlay){var e=this.document.data("ui-dialog-overlays")-1;e?this.document.data("ui-dialog-overlays",e):this.document.unbind("focusin").removeData("ui-dialog-overlays"),this.overlay.remove(),this.overlay=null}}}),e.widget("ui.progressbar",{version:"1.11.4",options:{max:100,value:0,change:null,complete:null},min:0,_create:function(){this.oldValue=this.options.value=this._constrainedValue(),this.element.addClass("ui-progressbar ui-widget ui-widget-content ui-corner-all").attr({role:"progressbar","aria-valuemin":this.min}),this.valueDiv=e("<div class='ui-progressbar-value ui-widget-header ui-corner-left'></div>").appendTo(this.element),this._refreshValue()},_destroy:function(){this.element.removeClass("ui-progressbar ui-widget ui-widget-content ui-corner-all").removeAttr("role").removeAttr("aria-valuemin").removeAttr("aria-valuemax").removeAttr("aria-valuenow"),this.valueDiv.remove()},value:function(e){return void 0===e?this.options.value:(this.options.value=this._constrainedValue(e),this._refreshValue(),void 0)},_constrainedValue:function(e){return void 0===e&&(e=this.options.value),this.indeterminate=e===!1,"number"!=typeof e&&(e=0),this.indeterminate?!1:Math.min(this.options.max,Math.max(this.min,e))},_setOptions:function(e){var t=e.value;delete e.value,this._super(e),this.options.value=this._constrainedValue(t),this._refreshValue()},_setOption:function(e,t){"max"===e&&(t=Math.max(this.min,t)),"disabled"===e&&this.element.toggleClass("ui-state-disabled",!!t).attr("aria-disabled",t),this._super(e,t)},_percentage:function(){return this.indeterminate?100:100*(this.options.value-this.min)/(this.options.max-this.min)},_refreshValue:function(){var t=this.options.value,i=this._percentage();this.valueDiv.toggle(this.indeterminate||t>this.min).toggleClass("ui-corner-right",t===this.options.max).width(i.toFixed(0)+"%"),this.element.toggleClass("ui-progressbar-indeterminate",this.indeterminate),this.indeterminate?(this.element.removeAttr("aria-valuenow"),this.overlayDiv||(this.overlayDiv=e("<div class='ui-progressbar-overlay'></div>").appendTo(this.valueDiv))):(this.element.attr({"aria-valuemax":this.options.max,"aria-valuenow":t}),this.overlayDiv&&(this.overlayDiv.remove(),this.overlayDiv=null)),this.oldValue!==t&&(this.oldValue=t,this._trigger("change")),t===this.options.max&&this._trigger("complete")}}),e.widget("ui.selectmenu",{version:"1.11.4",defaultElement:"<select>",options:{appendTo:null,disabled:null,icons:{button:"ui-icon-triangle-1-s"},position:{my:"left top",at:"left bottom",collision:"none"},width:null,change:null,close:null,focus:null,open:null,select:null},_create:function(){var e=this.element.uniqueId().attr("id");this.ids={element:e,button:e+"-button",menu:e+"-menu"},this._drawButton(),this._drawMenu(),this.options.disabled&&this.disable()},_drawButton:function(){var t=this;this.label=e("label[for='"+this.ids.element+"']").attr("for",this.ids.button),this._on(this.label,{click:function(e){this.button.focus(),e.preventDefault()}}),this.element.hide(),this.button=e("<span>",{"class":"ui-selectmenu-button ui-widget ui-state-default ui-corner-all",tabindex:this.options.disabled?-1:0,id:this.ids.button,role:"combobox","aria-expanded":"false","aria-autocomplete":"list","aria-owns":this.ids.menu,"aria-haspopup":"true"}).insertAfter(this.element),e("<span>",{"class":"ui-icon "+this.options.icons.button}).prependTo(this.button),this.buttonText=e("<span>",{"class":"ui-selectmenu-text"}).appendTo(this.button),this._setText(this.buttonText,this.element.find("option:selected").text()),this._resizeButton(),this._on(this.button,this._buttonEvents),this.button.one("focusin",function(){t.menuItems||t._refreshMenu()}),this._hoverable(this.button),this._focusable(this.button)},_drawMenu:function(){var t=this;this.menu=e("<ul>",{"aria-hidden":"true","aria-labelledby":this.ids.button,id:this.ids.menu}),this.menuWrap=e("<div>",{"class":"ui-selectmenu-menu ui-front"}).append(this.menu).appendTo(this._appendTo()),this.menuInstance=this.menu.menu({role:"listbox",select:function(e,i){e.preventDefault(),t._setSelection(),t._select(i.item.data("ui-selectmenu-item"),e)},focus:function(e,i){var s=i.item.data("ui-selectmenu-item");null!=t.focusIndex&&s.index!==t.focusIndex&&(t._trigger("focus",e,{item:s}),t.isOpen||t._select(s,e)),t.focusIndex=s.index,t.button.attr("aria-activedescendant",t.menuItems.eq(s.index).attr("id"))}}).menu("instance"),this.menu.addClass("ui-corner-bottom").removeClass("ui-corner-all"),this.menuInstance._off(this.menu,"mouseleave"),this.menuInstance._closeOnDocumentClick=function(){return!1},this.menuInstance._isDivider=function(){return!1}},refresh:function(){this._refreshMenu(),this._setText(this.buttonText,this._getSelectedItem().text()),this.options.width||this._resizeButton()},_refreshMenu:function(){this.menu.empty();var e,t=this.element.find("option");t.length&&(this._parseOptions(t),this._renderMenu(this.menu,this.items),this.menuInstance.refresh(),this.menuItems=this.menu.find("li").not(".ui-selectmenu-optgroup"),e=this._getSelectedItem(),this.menuInstance.focus(null,e),this._setAria(e.data("ui-selectmenu-item")),this._setOption("disabled",this.element.prop("disabled")))},open:function(e){this.options.disabled||(this.menuItems?(this.menu.find(".ui-state-focus").removeClass("ui-state-focus"),this.menuInstance.focus(null,this._getSelectedItem())):this._refreshMenu(),this.isOpen=!0,this._toggleAttr(),this._resizeMenu(),this._position(),this._on(this.document,this._documentClick),this._trigger("open",e))},_position:function(){this.menuWrap.position(e.extend({of:this.button},this.options.position))},close:function(e){this.isOpen&&(this.isOpen=!1,this._toggleAttr(),this.range=null,this._off(this.document),this._trigger("close",e))},widget:function(){return this.button},menuWidget:function(){return this.menu},_renderMenu:function(t,i){var s=this,n="";e.each(i,function(i,a){a.optgroup!==n&&(e("<li>",{"class":"ui-selectmenu-optgroup ui-menu-divider"+(a.element.parent("optgroup").prop("disabled")?" ui-state-disabled":""),text:a.optgroup}).appendTo(t),n=a.optgroup),s._renderItemData(t,a)})},_renderItemData:function(e,t){return this._renderItem(e,t).data("ui-selectmenu-item",t)},_renderItem:function(t,i){var s=e("<li>");return i.disabled&&s.addClass("ui-state-disabled"),this._setText(s,i.label),s.appendTo(t)},_setText:function(e,t){t?e.text(t):e.html("&#160;")},_move:function(e,t){var i,s,n=".ui-menu-item";this.isOpen?i=this.menuItems.eq(this.focusIndex):(i=this.menuItems.eq(this.element[0].selectedIndex),n+=":not(.ui-state-disabled)"),s="first"===e||"last"===e?i["first"===e?"prevAll":"nextAll"](n).eq(-1):i[e+"All"](n).eq(0),s.length&&this.menuInstance.focus(t,s)},_getSelectedItem:function(){return this.menuItems.eq(this.element[0].selectedIndex)},_toggle:function(e){this[this.isOpen?"close":"open"](e)},_setSelection:function(){var e;this.range&&(window.getSelection?(e=window.getSelection(),e.removeAllRanges(),e.addRange(this.range)):this.range.select(),this.button.focus())},_documentClick:{mousedown:function(t){this.isOpen&&(e(t.target).closest(".ui-selectmenu-menu, #"+this.ids.button).length||this.close(t))}},_buttonEvents:{mousedown:function(){var e;window.getSelection?(e=window.getSelection(),e.rangeCount&&(this.range=e.getRangeAt(0))):this.range=document.selection.createRange()},click:function(e){this._setSelection(),this._toggle(e)},keydown:function(t){var i=!0;switch(t.keyCode){case e.ui.keyCode.TAB:case e.ui.keyCode.ESCAPE:this.close(t),i=!1;break;case e.ui.keyCode.ENTER:this.isOpen&&this._selectFocusedItem(t);break;case e.ui.keyCode.UP:t.altKey?this._toggle(t):this._move("prev",t);break;case e.ui.keyCode.DOWN:t.altKey?this._toggle(t):this._move("next",t);break;case e.ui.keyCode.SPACE:this.isOpen?this._selectFocusedItem(t):this._toggle(t);break;case e.ui.keyCode.LEFT:this._move("prev",t);break;case e.ui.keyCode.RIGHT:this._move("next",t);break;case e.ui.keyCode.HOME:case e.ui.keyCode.PAGE_UP:this._move("first",t);break;case e.ui.keyCode.END:case e.ui.keyCode.PAGE_DOWN:this._move("last",t);break;default:this.menu.trigger(t),i=!1}i&&t.preventDefault()}},_selectFocusedItem:function(e){var t=this.menuItems.eq(this.focusIndex);t.hasClass("ui-state-disabled")||this._select(t.data("ui-selectmenu-item"),e)},_select:function(e,t){var i=this.element[0].selectedIndex;this.element[0].selectedIndex=e.index,this._setText(this.buttonText,e.label),this._setAria(e),this._trigger("select",t,{item:e}),e.index!==i&&this._trigger("change",t,{item:e}),this.close(t)},_setAria:function(e){var t=this.menuItems.eq(e.index).attr("id");this.button.attr({"aria-labelledby":t,"aria-activedescendant":t}),this.menu.attr("aria-activedescendant",t)},_setOption:function(e,t){"icons"===e&&this.button.find("span.ui-icon").removeClass(this.options.icons.button).addClass(t.button),this._super(e,t),"appendTo"===e&&this.menuWrap.appendTo(this._appendTo()),"disabled"===e&&(this.menuInstance.option("disabled",t),this.button.toggleClass("ui-state-disabled",t).attr("aria-disabled",t),this.element.prop("disabled",t),t?(this.button.attr("tabindex",-1),this.close()):this.button.attr("tabindex",0)),"width"===e&&this._resizeButton()},_appendTo:function(){var t=this.options.appendTo;return t&&(t=t.jquery||t.nodeType?e(t):this.document.find(t).eq(0)),t&&t[0]||(t=this.element.closest(".ui-front")),t.length||(t=this.document[0].body),t},_toggleAttr:function(){this.button.toggleClass("ui-corner-top",this.isOpen).toggleClass("ui-corner-all",!this.isOpen).attr("aria-expanded",this.isOpen),this.menuWrap.toggleClass("ui-selectmenu-open",this.isOpen),this.menu.attr("aria-hidden",!this.isOpen)},_resizeButton:function(){var e=this.options.width;e||(e=this.element.show().outerWidth(),this.element.hide()),this.button.outerWidth(e)},_resizeMenu:function(){this.menu.outerWidth(Math.max(this.button.outerWidth(),this.menu.width("").outerWidth()+1))},_getCreateOptions:function(){return{disabled:this.element.prop("disabled")}},_parseOptions:function(t){var i=[];t.each(function(t,s){var n=e(s),a=n.parent("optgroup");i.push({element:n,index:t,value:n.val(),label:n.text(),optgroup:a.attr("label")||"",disabled:a.prop("disabled")||n.prop("disabled")})}),this.items=i},_destroy:function(){this.menuWrap.remove(),this.button.remove(),this.element.show(),this.element.removeUniqueId(),this.label.attr("for",this.ids.element)}}),e.widget("ui.slider",e.ui.mouse,{version:"1.11.4",widgetEventPrefix:"slide",options:{animate:!1,distance:0,max:100,min:0,orientation:"horizontal",range:!1,step:1,value:0,values:null,change:null,slide:null,start:null,stop:null},numPages:5,_create:function(){this._keySliding=!1,this._mouseSliding=!1,this._animateOff=!0,this._handleIndex=null,this._detectOrientation(),this._mouseInit(),this._calculateNewMax(),this.element.addClass("ui-slider ui-slider-"+this.orientation+" ui-widget"+" ui-widget-content"+" ui-corner-all"),this._refresh(),this._setOption("disabled",this.options.disabled),this._animateOff=!1},_refresh:function(){this._createRange(),this._createHandles(),this._setupEvents(),this._refreshValue()},_createHandles:function(){var t,i,s=this.options,n=this.element.find(".ui-slider-handle").addClass("ui-state-default ui-corner-all"),a="<span class='ui-slider-handle ui-state-default ui-corner-all' tabindex='0'></span>",o=[];for(i=s.values&&s.values.length||1,n.length>i&&(n.slice(i).remove(),n=n.slice(0,i)),t=n.length;i>t;t++)o.push(a);this.handles=n.add(e(o.join("")).appendTo(this.element)),this.handle=this.handles.eq(0),this.handles.each(function(t){e(this).data("ui-slider-handle-index",t)})},_createRange:function(){var t=this.options,i="";t.range?(t.range===!0&&(t.values?t.values.length&&2!==t.values.length?t.values=[t.values[0],t.values[0]]:e.isArray(t.values)&&(t.values=t.values.slice(0)):t.values=[this._valueMin(),this._valueMin()]),this.range&&this.range.length?this.range.removeClass("ui-slider-range-min ui-slider-range-max").css({left:"",bottom:""}):(this.range=e("<div></div>").appendTo(this.element),i="ui-slider-range ui-widget-header ui-corner-all"),this.range.addClass(i+("min"===t.range||"max"===t.range?" ui-slider-range-"+t.range:""))):(this.range&&this.range.remove(),this.range=null)},_setupEvents:function(){this._off(this.handles),this._on(this.handles,this._handleEvents),this._hoverable(this.handles),this._focusable(this.handles)},_destroy:function(){this.handles.remove(),this.range&&this.range.remove(),this.element.removeClass("ui-slider ui-slider-horizontal ui-slider-vertical ui-widget ui-widget-content ui-corner-all"),this._mouseDestroy()},_mouseCapture:function(t){var i,s,n,a,o,r,h,l,u=this,d=this.options;return d.disabled?!1:(this.elementSize={width:this.element.outerWidth(),height:this.element.outerHeight()},this.elementOffset=this.element.offset(),i={x:t.pageX,y:t.pageY},s=this._normValueFromMouse(i),n=this._valueMax()-this._valueMin()+1,this.handles.each(function(t){var i=Math.abs(s-u.values(t));(n>i||n===i&&(t===u._lastChangedValue||u.values(t)===d.min))&&(n=i,a=e(this),o=t)}),r=this._start(t,o),r===!1?!1:(this._mouseSliding=!0,this._handleIndex=o,a.addClass("ui-state-active").focus(),h=a.offset(),l=!e(t.target).parents().addBack().is(".ui-slider-handle"),this._clickOffset=l?{left:0,top:0}:{left:t.pageX-h.left-a.width()/2,top:t.pageY-h.top-a.height()/2-(parseInt(a.css("borderTopWidth"),10)||0)-(parseInt(a.css("borderBottomWidth"),10)||0)+(parseInt(a.css("marginTop"),10)||0)},this.handles.hasClass("ui-state-hover")||this._slide(t,o,s),this._animateOff=!0,!0))},_mouseStart:function(){return!0},_mouseDrag:function(e){var t={x:e.pageX,y:e.pageY},i=this._normValueFromMouse(t);return this._slide(e,this._handleIndex,i),!1},_mouseStop:function(e){return this.handles.removeClass("ui-state-active"),this._mouseSliding=!1,this._stop(e,this._handleIndex),this._change(e,this._handleIndex),this._handleIndex=null,this._clickOffset=null,this._animateOff=!1,!1},_detectOrientation:function(){this.orientation="vertical"===this.options.orientation?"vertical":"horizontal"},_normValueFromMouse:function(e){var t,i,s,n,a;return"horizontal"===this.orientation?(t=this.elementSize.width,i=e.x-this.elementOffset.left-(this._clickOffset?this._clickOffset.left:0)):(t=this.elementSize.height,i=e.y-this.elementOffset.top-(this._clickOffset?this._clickOffset.top:0)),s=i/t,s>1&&(s=1),0>s&&(s=0),"vertical"===this.orientation&&(s=1-s),n=this._valueMax()-this._valueMin(),a=this._valueMin()+s*n,this._trimAlignValue(a)},_start:function(e,t){var i={handle:this.handles[t],value:this.value()};return this.options.values&&this.options.values.length&&(i.value=this.values(t),i.values=this.values()),this._trigger("start",e,i)},_slide:function(e,t,i){var s,n,a;this.options.values&&this.options.values.length?(s=this.values(t?0:1),2===this.options.values.length&&this.options.range===!0&&(0===t&&i>s||1===t&&s>i)&&(i=s),i!==this.values(t)&&(n=this.values(),n[t]=i,a=this._trigger("slide",e,{handle:this.handles[t],value:i,values:n}),s=this.values(t?0:1),a!==!1&&this.values(t,i))):i!==this.value()&&(a=this._trigger("slide",e,{handle:this.handles[t],value:i}),a!==!1&&this.value(i))},_stop:function(e,t){var i={handle:this.handles[t],value:this.value()};this.options.values&&this.options.values.length&&(i.value=this.values(t),i.values=this.values()),this._trigger("stop",e,i)},_change:function(e,t){if(!this._keySliding&&!this._mouseSliding){var i={handle:this.handles[t],value:this.value()};this.options.values&&this.options.values.length&&(i.value=this.values(t),i.values=this.values()),this._lastChangedValue=t,this._trigger("change",e,i)}},value:function(e){return arguments.length?(this.options.value=this._trimAlignValue(e),this._refreshValue(),this._change(null,0),void 0):this._value()},values:function(t,i){var s,n,a;if(arguments.length>1)return this.options.values[t]=this._trimAlignValue(i),this._refreshValue(),this._change(null,t),void 0;if(!arguments.length)return this._values();if(!e.isArray(arguments[0]))return this.options.values&&this.options.values.length?this._values(t):this.value();for(s=this.options.values,n=arguments[0],a=0;s.length>a;a+=1)s[a]=this._trimAlignValue(n[a]),this._change(null,a);this._refreshValue()},_setOption:function(t,i){var s,n=0;switch("range"===t&&this.options.range===!0&&("min"===i?(this.options.value=this._values(0),this.options.values=null):"max"===i&&(this.options.value=this._values(this.options.values.length-1),this.options.values=null)),e.isArray(this.options.values)&&(n=this.options.values.length),"disabled"===t&&this.element.toggleClass("ui-state-disabled",!!i),this._super(t,i),t){case"orientation":this._detectOrientation(),this.element.removeClass("ui-slider-horizontal ui-slider-vertical").addClass("ui-slider-"+this.orientation),this._refreshValue(),this.handles.css("horizontal"===i?"bottom":"left","");break;case"value":this._animateOff=!0,this._refreshValue(),this._change(null,0),this._animateOff=!1;break;case"values":for(this._animateOff=!0,this._refreshValue(),s=0;n>s;s+=1)this._change(null,s);this._animateOff=!1;break;case"step":case"min":case"max":this._animateOff=!0,this._calculateNewMax(),this._refreshValue(),this._animateOff=!1;break;case"range":this._animateOff=!0,this._refresh(),this._animateOff=!1}},_value:function(){var e=this.options.value;return e=this._trimAlignValue(e)},_values:function(e){var t,i,s;if(arguments.length)return t=this.options.values[e],t=this._trimAlignValue(t);if(this.options.values&&this.options.values.length){for(i=this.options.values.slice(),s=0;i.length>s;s+=1)i[s]=this._trimAlignValue(i[s]);return i}return[]},_trimAlignValue:function(e){if(this._valueMin()>=e)return this._valueMin();if(e>=this._valueMax())return this._valueMax();var t=this.options.step>0?this.options.step:1,i=(e-this._valueMin())%t,s=e-i;return 2*Math.abs(i)>=t&&(s+=i>0?t:-t),parseFloat(s.toFixed(5))},_calculateNewMax:function(){var e=this.options.max,t=this._valueMin(),i=this.options.step,s=Math.floor(+(e-t).toFixed(this._precision())/i)*i;e=s+t,this.max=parseFloat(e.toFixed(this._precision()))},_precision:function(){var e=this._precisionOf(this.options.step);return null!==this.options.min&&(e=Math.max(e,this._precisionOf(this.options.min))),e},_precisionOf:function(e){var t=""+e,i=t.indexOf(".");return-1===i?0:t.length-i-1},_valueMin:function(){return this.options.min},_valueMax:function(){return this.max},_refreshValue:function(){var t,i,s,n,a,o=this.options.range,r=this.options,h=this,l=this._animateOff?!1:r.animate,u={};this.options.values&&this.options.values.length?this.handles.each(function(s){i=100*((h.values(s)-h._valueMin())/(h._valueMax()-h._valueMin())),u["horizontal"===h.orientation?"left":"bottom"]=i+"%",e(this).stop(1,1)[l?"animate":"css"](u,r.animate),h.options.range===!0&&("horizontal"===h.orientation?(0===s&&h.range.stop(1,1)[l?"animate":"css"]({left:i+"%"},r.animate),1===s&&h.range[l?"animate":"css"]({width:i-t+"%"},{queue:!1,duration:r.animate})):(0===s&&h.range.stop(1,1)[l?"animate":"css"]({bottom:i+"%"},r.animate),1===s&&h.range[l?"animate":"css"]({height:i-t+"%"},{queue:!1,duration:r.animate}))),t=i}):(s=this.value(),n=this._valueMin(),a=this._valueMax(),i=a!==n?100*((s-n)/(a-n)):0,u["horizontal"===this.orientation?"left":"bottom"]=i+"%",this.handle.stop(1,1)[l?"animate":"css"](u,r.animate),"min"===o&&"horizontal"===this.orientation&&this.range.stop(1,1)[l?"animate":"css"]({width:i+"%"},r.animate),"max"===o&&"horizontal"===this.orientation&&this.range[l?"animate":"css"]({width:100-i+"%"},{queue:!1,duration:r.animate}),"min"===o&&"vertical"===this.orientation&&this.range.stop(1,1)[l?"animate":"css"]({height:i+"%"},r.animate),"max"===o&&"vertical"===this.orientation&&this.range[l?"animate":"css"]({height:100-i+"%"},{queue:!1,duration:r.animate}))},_handleEvents:{keydown:function(t){var i,s,n,a,o=e(t.target).data("ui-slider-handle-index");switch(t.keyCode){case e.ui.keyCode.HOME:case e.ui.keyCode.END:case e.ui.keyCode.PAGE_UP:case e.ui.keyCode.PAGE_DOWN:case e.ui.keyCode.UP:case e.ui.keyCode.RIGHT:case e.ui.keyCode.DOWN:case e.ui.keyCode.LEFT:if(t.preventDefault(),!this._keySliding&&(this._keySliding=!0,e(t.target).addClass("ui-state-active"),i=this._start(t,o),i===!1))return}switch(a=this.options.step,s=n=this.options.values&&this.options.values.length?this.values(o):this.value(),t.keyCode){case e.ui.keyCode.HOME:n=this._valueMin();break;case e.ui.keyCode.END:n=this._valueMax();break;case e.ui.keyCode.PAGE_UP:n=this._trimAlignValue(s+(this._valueMax()-this._valueMin())/this.numPages);break;case e.ui.keyCode.PAGE_DOWN:n=this._trimAlignValue(s-(this._valueMax()-this._valueMin())/this.numPages);break;case e.ui.keyCode.UP:case e.ui.keyCode.RIGHT:if(s===this._valueMax())return;n=this._trimAlignValue(s+a);break;case e.ui.keyCode.DOWN:case e.ui.keyCode.LEFT:if(s===this._valueMin())return;n=this._trimAlignValue(s-a)}this._slide(t,o,n)},keyup:function(t){var i=e(t.target).data("ui-slider-handle-index");this._keySliding&&(this._keySliding=!1,this._stop(t,i),this._change(t,i),e(t.target).removeClass("ui-state-active"))}}}),e.widget("ui.spinner",{version:"1.11.4",defaultElement:"<input>",widgetEventPrefix:"spin",options:{culture:null,icons:{down:"ui-icon-triangle-1-s",up:"ui-icon-triangle-1-n"},incremental:!0,max:null,min:null,numberFormat:null,page:10,step:1,change:null,spin:null,start:null,stop:null},_create:function(){this._setOption("max",this.options.max),this._setOption("min",this.options.min),this._setOption("step",this.options.step),""!==this.value()&&this._value(this.element.val(),!0),this._draw(),this._on(this._events),this._refresh(),this._on(this.window,{beforeunload:function(){this.element.removeAttr("autocomplete")}})},_getCreateOptions:function(){var t={},i=this.element;return e.each(["min","max","step"],function(e,s){var n=i.attr(s);void 0!==n&&n.length&&(t[s]=n)}),t},_events:{keydown:function(e){this._start(e)&&this._keydown(e)&&e.preventDefault()},keyup:"_stop",focus:function(){this.previous=this.element.val()},blur:function(e){return this.cancelBlur?(delete this.cancelBlur,void 0):(this._stop(),this._refresh(),this.previous!==this.element.val()&&this._trigger("change",e),void 0)},mousewheel:function(e,t){if(t){if(!this.spinning&&!this._start(e))return!1;this._spin((t>0?1:-1)*this.options.step,e),clearTimeout(this.mousewheelTimer),this.mousewheelTimer=this._delay(function(){this.spinning&&this._stop(e)},100),e.preventDefault()}},"mousedown .ui-spinner-button":function(t){function i(){var e=this.element[0]===this.document[0].activeElement;e||(this.element.focus(),this.previous=s,this._delay(function(){this.previous=s}))}var s;s=this.element[0]===this.document[0].activeElement?this.previous:this.element.val(),t.preventDefault(),i.call(this),this.cancelBlur=!0,this._delay(function(){delete this.cancelBlur,i.call(this)}),this._start(t)!==!1&&this._repeat(null,e(t.currentTarget).hasClass("ui-spinner-up")?1:-1,t)},"mouseup .ui-spinner-button":"_stop","mouseenter .ui-spinner-button":function(t){return e(t.currentTarget).hasClass("ui-state-active")?this._start(t)===!1?!1:(this._repeat(null,e(t.currentTarget).hasClass("ui-spinner-up")?1:-1,t),void 0):void 0},"mouseleave .ui-spinner-button":"_stop"},_draw:function(){var e=this.uiSpinner=this.element.addClass("ui-spinner-input").attr("autocomplete","off").wrap(this._uiSpinnerHtml()).parent().append(this._buttonHtml());this.element.attr("role","spinbutton"),this.buttons=e.find(".ui-spinner-button").attr("tabIndex",-1).button().removeClass("ui-corner-all"),this.buttons.height()>Math.ceil(.5*e.height())&&e.height()>0&&e.height(e.height()),this.options.disabled&&this.disable()},_keydown:function(t){var i=this.options,s=e.ui.keyCode;switch(t.keyCode){case s.UP:return this._repeat(null,1,t),!0;case s.DOWN:return this._repeat(null,-1,t),!0;case s.PAGE_UP:return this._repeat(null,i.page,t),!0;case s.PAGE_DOWN:return this._repeat(null,-i.page,t),!0}return!1},_uiSpinnerHtml:function(){return"<span class='ui-spinner ui-widget ui-widget-content ui-corner-all'></span>"},_buttonHtml:function(){return"<a class='ui-spinner-button ui-spinner-up ui-corner-tr'><span class='ui-icon "+this.options.icons.up+"'>&#9650;</span>"+"</a>"+"<a class='ui-spinner-button ui-spinner-down ui-corner-br'>"+"<span class='ui-icon "+this.options.icons.down+"'>&#9660;</span>"+"</a>"},_start:function(e){return this.spinning||this._trigger("start",e)!==!1?(this.counter||(this.counter=1),this.spinning=!0,!0):!1},_repeat:function(e,t,i){e=e||500,clearTimeout(this.timer),this.timer=this._delay(function(){this._repeat(40,t,i)},e),this._spin(t*this.options.step,i)},_spin:function(e,t){var i=this.value()||0;this.counter||(this.counter=1),i=this._adjustValue(i+e*this._increment(this.counter)),this.spinning&&this._trigger("spin",t,{value:i})===!1||(this._value(i),this.counter++)},_increment:function(t){var i=this.options.incremental;return i?e.isFunction(i)?i(t):Math.floor(t*t*t/5e4-t*t/500+17*t/200+1):1},_precision:function(){var e=this._precisionOf(this.options.step);return null!==this.options.min&&(e=Math.max(e,this._precisionOf(this.options.min))),e},_precisionOf:function(e){var t=""+e,i=t.indexOf(".");return-1===i?0:t.length-i-1},_adjustValue:function(e){var t,i,s=this.options;return t=null!==s.min?s.min:0,i=e-t,i=Math.round(i/s.step)*s.step,e=t+i,e=parseFloat(e.toFixed(this._precision())),null!==s.max&&e>s.max?s.max:null!==s.min&&s.min>e?s.min:e},_stop:function(e){this.spinning&&(clearTimeout(this.timer),clearTimeout(this.mousewheelTimer),this.counter=0,this.spinning=!1,this._trigger("stop",e))},_setOption:function(e,t){if("culture"===e||"numberFormat"===e){var i=this._parse(this.element.val());return this.options[e]=t,this.element.val(this._format(i)),void 0}("max"===e||"min"===e||"step"===e)&&"string"==typeof t&&(t=this._parse(t)),"icons"===e&&(this.buttons.first().find(".ui-icon").removeClass(this.options.icons.up).addClass(t.up),this.buttons.last().find(".ui-icon").removeClass(this.options.icons.down).addClass(t.down)),this._super(e,t),"disabled"===e&&(this.widget().toggleClass("ui-state-disabled",!!t),this.element.prop("disabled",!!t),this.buttons.button(t?"disable":"enable"))},_setOptions:s(function(e){this._super(e)}),_parse:function(e){return"string"==typeof e&&""!==e&&(e=window.Globalize&&this.options.numberFormat?Globalize.parseFloat(e,10,this.options.culture):+e),""===e||isNaN(e)?null:e
},_format:function(e){return""===e?"":window.Globalize&&this.options.numberFormat?Globalize.format(e,this.options.numberFormat,this.options.culture):e},_refresh:function(){this.element.attr({"aria-valuemin":this.options.min,"aria-valuemax":this.options.max,"aria-valuenow":this._parse(this.element.val())})},isValid:function(){var e=this.value();return null===e?!1:e===this._adjustValue(e)},_value:function(e,t){var i;""!==e&&(i=this._parse(e),null!==i&&(t||(i=this._adjustValue(i)),e=this._format(i))),this.element.val(e),this._refresh()},_destroy:function(){this.element.removeClass("ui-spinner-input").prop("disabled",!1).removeAttr("autocomplete").removeAttr("role").removeAttr("aria-valuemin").removeAttr("aria-valuemax").removeAttr("aria-valuenow"),this.uiSpinner.replaceWith(this.element)},stepUp:s(function(e){this._stepUp(e)}),_stepUp:function(e){this._start()&&(this._spin((e||1)*this.options.step),this._stop())},stepDown:s(function(e){this._stepDown(e)}),_stepDown:function(e){this._start()&&(this._spin((e||1)*-this.options.step),this._stop())},pageUp:s(function(e){this._stepUp((e||1)*this.options.page)}),pageDown:s(function(e){this._stepDown((e||1)*this.options.page)}),value:function(e){return arguments.length?(s(this._value).call(this,e),void 0):this._parse(this.element.val())},widget:function(){return this.uiSpinner}}),e.widget("ui.tabs",{version:"1.11.4",delay:300,options:{active:null,collapsible:!1,event:"click",heightStyle:"content",hide:null,show:null,activate:null,beforeActivate:null,beforeLoad:null,load:null},_isLocal:function(){var e=/#.*$/;return function(t){var i,s;t=t.cloneNode(!1),i=t.href.replace(e,""),s=location.href.replace(e,"");try{i=decodeURIComponent(i)}catch(n){}try{s=decodeURIComponent(s)}catch(n){}return t.hash.length>1&&i===s}}(),_create:function(){var t=this,i=this.options;this.running=!1,this.element.addClass("ui-tabs ui-widget ui-widget-content ui-corner-all").toggleClass("ui-tabs-collapsible",i.collapsible),this._processTabs(),i.active=this._initialActive(),e.isArray(i.disabled)&&(i.disabled=e.unique(i.disabled.concat(e.map(this.tabs.filter(".ui-state-disabled"),function(e){return t.tabs.index(e)}))).sort()),this.active=this.options.active!==!1&&this.anchors.length?this._findActive(i.active):e(),this._refresh(),this.active.length&&this.load(i.active)},_initialActive:function(){var t=this.options.active,i=this.options.collapsible,s=location.hash.substring(1);return null===t&&(s&&this.tabs.each(function(i,n){return e(n).attr("aria-controls")===s?(t=i,!1):void 0}),null===t&&(t=this.tabs.index(this.tabs.filter(".ui-tabs-active"))),(null===t||-1===t)&&(t=this.tabs.length?0:!1)),t!==!1&&(t=this.tabs.index(this.tabs.eq(t)),-1===t&&(t=i?!1:0)),!i&&t===!1&&this.anchors.length&&(t=0),t},_getCreateEventData:function(){return{tab:this.active,panel:this.active.length?this._getPanelForTab(this.active):e()}},_tabKeydown:function(t){var i=e(this.document[0].activeElement).closest("li"),s=this.tabs.index(i),n=!0;if(!this._handlePageNav(t)){switch(t.keyCode){case e.ui.keyCode.RIGHT:case e.ui.keyCode.DOWN:s++;break;case e.ui.keyCode.UP:case e.ui.keyCode.LEFT:n=!1,s--;break;case e.ui.keyCode.END:s=this.anchors.length-1;break;case e.ui.keyCode.HOME:s=0;break;case e.ui.keyCode.SPACE:return t.preventDefault(),clearTimeout(this.activating),this._activate(s),void 0;case e.ui.keyCode.ENTER:return t.preventDefault(),clearTimeout(this.activating),this._activate(s===this.options.active?!1:s),void 0;default:return}t.preventDefault(),clearTimeout(this.activating),s=this._focusNextTab(s,n),t.ctrlKey||t.metaKey||(i.attr("aria-selected","false"),this.tabs.eq(s).attr("aria-selected","true"),this.activating=this._delay(function(){this.option("active",s)},this.delay))}},_panelKeydown:function(t){this._handlePageNav(t)||t.ctrlKey&&t.keyCode===e.ui.keyCode.UP&&(t.preventDefault(),this.active.focus())},_handlePageNav:function(t){return t.altKey&&t.keyCode===e.ui.keyCode.PAGE_UP?(this._activate(this._focusNextTab(this.options.active-1,!1)),!0):t.altKey&&t.keyCode===e.ui.keyCode.PAGE_DOWN?(this._activate(this._focusNextTab(this.options.active+1,!0)),!0):void 0},_findNextTab:function(t,i){function s(){return t>n&&(t=0),0>t&&(t=n),t}for(var n=this.tabs.length-1;-1!==e.inArray(s(),this.options.disabled);)t=i?t+1:t-1;return t},_focusNextTab:function(e,t){return e=this._findNextTab(e,t),this.tabs.eq(e).focus(),e},_setOption:function(e,t){return"active"===e?(this._activate(t),void 0):"disabled"===e?(this._setupDisabled(t),void 0):(this._super(e,t),"collapsible"===e&&(this.element.toggleClass("ui-tabs-collapsible",t),t||this.options.active!==!1||this._activate(0)),"event"===e&&this._setupEvents(t),"heightStyle"===e&&this._setupHeightStyle(t),void 0)},_sanitizeSelector:function(e){return e?e.replace(/[!"$%&'()*+,.\/:;<=>?@\[\]\^`{|}~]/g,"\\$&"):""},refresh:function(){var t=this.options,i=this.tablist.children(":has(a[href])");t.disabled=e.map(i.filter(".ui-state-disabled"),function(e){return i.index(e)}),this._processTabs(),t.active!==!1&&this.anchors.length?this.active.length&&!e.contains(this.tablist[0],this.active[0])?this.tabs.length===t.disabled.length?(t.active=!1,this.active=e()):this._activate(this._findNextTab(Math.max(0,t.active-1),!1)):t.active=this.tabs.index(this.active):(t.active=!1,this.active=e()),this._refresh()},_refresh:function(){this._setupDisabled(this.options.disabled),this._setupEvents(this.options.event),this._setupHeightStyle(this.options.heightStyle),this.tabs.not(this.active).attr({"aria-selected":"false","aria-expanded":"false",tabIndex:-1}),this.panels.not(this._getPanelForTab(this.active)).hide().attr({"aria-hidden":"true"}),this.active.length?(this.active.addClass("ui-tabs-active ui-state-active").attr({"aria-selected":"true","aria-expanded":"true",tabIndex:0}),this._getPanelForTab(this.active).show().attr({"aria-hidden":"false"})):this.tabs.eq(0).attr("tabIndex",0)},_processTabs:function(){var t=this,i=this.tabs,s=this.anchors,n=this.panels;this.tablist=this._getList().addClass("ui-tabs-nav ui-helper-reset ui-helper-clearfix ui-widget-header ui-corner-all").attr("role","tablist").delegate("> li","mousedown"+this.eventNamespace,function(t){e(this).is(".ui-state-disabled")&&t.preventDefault()}).delegate(".ui-tabs-anchor","focus"+this.eventNamespace,function(){e(this).closest("li").is(".ui-state-disabled")&&this.blur()}),this.tabs=this.tablist.find("> li:has(a[href])").addClass("ui-state-default ui-corner-top").attr({role:"tab",tabIndex:-1}),this.anchors=this.tabs.map(function(){return e("a",this)[0]}).addClass("ui-tabs-anchor").attr({role:"presentation",tabIndex:-1}),this.panels=e(),this.anchors.each(function(i,s){var n,a,o,r=e(s).uniqueId().attr("id"),h=e(s).closest("li"),l=h.attr("aria-controls");t._isLocal(s)?(n=s.hash,o=n.substring(1),a=t.element.find(t._sanitizeSelector(n))):(o=h.attr("aria-controls")||e({}).uniqueId()[0].id,n="#"+o,a=t.element.find(n),a.length||(a=t._createPanel(o),a.insertAfter(t.panels[i-1]||t.tablist)),a.attr("aria-live","polite")),a.length&&(t.panels=t.panels.add(a)),l&&h.data("ui-tabs-aria-controls",l),h.attr({"aria-controls":o,"aria-labelledby":r}),a.attr("aria-labelledby",r)}),this.panels.addClass("ui-tabs-panel ui-widget-content ui-corner-bottom").attr("role","tabpanel"),i&&(this._off(i.not(this.tabs)),this._off(s.not(this.anchors)),this._off(n.not(this.panels)))},_getList:function(){return this.tablist||this.element.find("ol,ul").eq(0)},_createPanel:function(t){return e("<div>").attr("id",t).addClass("ui-tabs-panel ui-widget-content ui-corner-bottom").data("ui-tabs-destroy",!0)},_setupDisabled:function(t){e.isArray(t)&&(t.length?t.length===this.anchors.length&&(t=!0):t=!1);for(var i,s=0;i=this.tabs[s];s++)t===!0||-1!==e.inArray(s,t)?e(i).addClass("ui-state-disabled").attr("aria-disabled","true"):e(i).removeClass("ui-state-disabled").removeAttr("aria-disabled");this.options.disabled=t},_setupEvents:function(t){var i={};t&&e.each(t.split(" "),function(e,t){i[t]="_eventHandler"}),this._off(this.anchors.add(this.tabs).add(this.panels)),this._on(!0,this.anchors,{click:function(e){e.preventDefault()}}),this._on(this.anchors,i),this._on(this.tabs,{keydown:"_tabKeydown"}),this._on(this.panels,{keydown:"_panelKeydown"}),this._focusable(this.tabs),this._hoverable(this.tabs)},_setupHeightStyle:function(t){var i,s=this.element.parent();"fill"===t?(i=s.height(),i-=this.element.outerHeight()-this.element.height(),this.element.siblings(":visible").each(function(){var t=e(this),s=t.css("position");"absolute"!==s&&"fixed"!==s&&(i-=t.outerHeight(!0))}),this.element.children().not(this.panels).each(function(){i-=e(this).outerHeight(!0)}),this.panels.each(function(){e(this).height(Math.max(0,i-e(this).innerHeight()+e(this).height()))}).css("overflow","auto")):"auto"===t&&(i=0,this.panels.each(function(){i=Math.max(i,e(this).height("").height())}).height(i))},_eventHandler:function(t){var i=this.options,s=this.active,n=e(t.currentTarget),a=n.closest("li"),o=a[0]===s[0],r=o&&i.collapsible,h=r?e():this._getPanelForTab(a),l=s.length?this._getPanelForTab(s):e(),u={oldTab:s,oldPanel:l,newTab:r?e():a,newPanel:h};t.preventDefault(),a.hasClass("ui-state-disabled")||a.hasClass("ui-tabs-loading")||this.running||o&&!i.collapsible||this._trigger("beforeActivate",t,u)===!1||(i.active=r?!1:this.tabs.index(a),this.active=o?e():a,this.xhr&&this.xhr.abort(),l.length||h.length||e.error("jQuery UI Tabs: Mismatching fragment identifier."),h.length&&this.load(this.tabs.index(a),t),this._toggle(t,u))},_toggle:function(t,i){function s(){a.running=!1,a._trigger("activate",t,i)}function n(){i.newTab.closest("li").addClass("ui-tabs-active ui-state-active"),o.length&&a.options.show?a._show(o,a.options.show,s):(o.show(),s())}var a=this,o=i.newPanel,r=i.oldPanel;this.running=!0,r.length&&this.options.hide?this._hide(r,this.options.hide,function(){i.oldTab.closest("li").removeClass("ui-tabs-active ui-state-active"),n()}):(i.oldTab.closest("li").removeClass("ui-tabs-active ui-state-active"),r.hide(),n()),r.attr("aria-hidden","true"),i.oldTab.attr({"aria-selected":"false","aria-expanded":"false"}),o.length&&r.length?i.oldTab.attr("tabIndex",-1):o.length&&this.tabs.filter(function(){return 0===e(this).attr("tabIndex")}).attr("tabIndex",-1),o.attr("aria-hidden","false"),i.newTab.attr({"aria-selected":"true","aria-expanded":"true",tabIndex:0})},_activate:function(t){var i,s=this._findActive(t);s[0]!==this.active[0]&&(s.length||(s=this.active),i=s.find(".ui-tabs-anchor")[0],this._eventHandler({target:i,currentTarget:i,preventDefault:e.noop}))},_findActive:function(t){return t===!1?e():this.tabs.eq(t)},_getIndex:function(e){return"string"==typeof e&&(e=this.anchors.index(this.anchors.filter("[href$='"+e+"']"))),e},_destroy:function(){this.xhr&&this.xhr.abort(),this.element.removeClass("ui-tabs ui-widget ui-widget-content ui-corner-all ui-tabs-collapsible"),this.tablist.removeClass("ui-tabs-nav ui-helper-reset ui-helper-clearfix ui-widget-header ui-corner-all").removeAttr("role"),this.anchors.removeClass("ui-tabs-anchor").removeAttr("role").removeAttr("tabIndex").removeUniqueId(),this.tablist.unbind(this.eventNamespace),this.tabs.add(this.panels).each(function(){e.data(this,"ui-tabs-destroy")?e(this).remove():e(this).removeClass("ui-state-default ui-state-active ui-state-disabled ui-corner-top ui-corner-bottom ui-widget-content ui-tabs-active ui-tabs-panel").removeAttr("tabIndex").removeAttr("aria-live").removeAttr("aria-busy").removeAttr("aria-selected").removeAttr("aria-labelledby").removeAttr("aria-hidden").removeAttr("aria-expanded").removeAttr("role")}),this.tabs.each(function(){var t=e(this),i=t.data("ui-tabs-aria-controls");i?t.attr("aria-controls",i).removeData("ui-tabs-aria-controls"):t.removeAttr("aria-controls")}),this.panels.show(),"content"!==this.options.heightStyle&&this.panels.css("height","")},enable:function(t){var i=this.options.disabled;i!==!1&&(void 0===t?i=!1:(t=this._getIndex(t),i=e.isArray(i)?e.map(i,function(e){return e!==t?e:null}):e.map(this.tabs,function(e,i){return i!==t?i:null})),this._setupDisabled(i))},disable:function(t){var i=this.options.disabled;if(i!==!0){if(void 0===t)i=!0;else{if(t=this._getIndex(t),-1!==e.inArray(t,i))return;i=e.isArray(i)?e.merge([t],i).sort():[t]}this._setupDisabled(i)}},load:function(t,i){t=this._getIndex(t);var s=this,n=this.tabs.eq(t),a=n.find(".ui-tabs-anchor"),o=this._getPanelForTab(n),r={tab:n,panel:o},h=function(e,t){"abort"===t&&s.panels.stop(!1,!0),n.removeClass("ui-tabs-loading"),o.removeAttr("aria-busy"),e===s.xhr&&delete s.xhr};this._isLocal(a[0])||(this.xhr=e.ajax(this._ajaxSettings(a,i,r)),this.xhr&&"canceled"!==this.xhr.statusText&&(n.addClass("ui-tabs-loading"),o.attr("aria-busy","true"),this.xhr.done(function(e,t,n){setTimeout(function(){o.html(e),s._trigger("load",i,r),h(n,t)},1)}).fail(function(e,t){setTimeout(function(){h(e,t)},1)})))},_ajaxSettings:function(t,i,s){var n=this;return{url:t.attr("href"),beforeSend:function(t,a){return n._trigger("beforeLoad",i,e.extend({jqXHR:t,ajaxSettings:a},s))}}},_getPanelForTab:function(t){var i=e(t).attr("aria-controls");return this.element.find(this._sanitizeSelector("#"+i))}}),e.widget("ui.tooltip",{version:"1.11.4",options:{content:function(){var t=e(this).attr("title")||"";return e("<a>").text(t).html()},hide:!0,items:"[title]:not([disabled])",position:{my:"left top+15",at:"left bottom",collision:"flipfit flip"},show:!0,tooltipClass:null,track:!1,close:null,open:null},_addDescribedBy:function(t,i){var s=(t.attr("aria-describedby")||"").split(/\s+/);s.push(i),t.data("ui-tooltip-id",i).attr("aria-describedby",e.trim(s.join(" ")))},_removeDescribedBy:function(t){var i=t.data("ui-tooltip-id"),s=(t.attr("aria-describedby")||"").split(/\s+/),n=e.inArray(i,s);-1!==n&&s.splice(n,1),t.removeData("ui-tooltip-id"),s=e.trim(s.join(" ")),s?t.attr("aria-describedby",s):t.removeAttr("aria-describedby")},_create:function(){this._on({mouseover:"open",focusin:"open"}),this.tooltips={},this.parents={},this.options.disabled&&this._disable(),this.liveRegion=e("<div>").attr({role:"log","aria-live":"assertive","aria-relevant":"additions"}).addClass("ui-helper-hidden-accessible").appendTo(this.document[0].body)},_setOption:function(t,i){var s=this;return"disabled"===t?(this[i?"_disable":"_enable"](),this.options[t]=i,void 0):(this._super(t,i),"content"===t&&e.each(this.tooltips,function(e,t){s._updateContent(t.element)}),void 0)},_disable:function(){var t=this;e.each(this.tooltips,function(i,s){var n=e.Event("blur");n.target=n.currentTarget=s.element[0],t.close(n,!0)}),this.element.find(this.options.items).addBack().each(function(){var t=e(this);t.is("[title]")&&t.data("ui-tooltip-title",t.attr("title")).removeAttr("title")})},_enable:function(){this.element.find(this.options.items).addBack().each(function(){var t=e(this);t.data("ui-tooltip-title")&&t.attr("title",t.data("ui-tooltip-title"))})},open:function(t){var i=this,s=e(t?t.target:this.element).closest(this.options.items);s.length&&!s.data("ui-tooltip-id")&&(s.attr("title")&&s.data("ui-tooltip-title",s.attr("title")),s.data("ui-tooltip-open",!0),t&&"mouseover"===t.type&&s.parents().each(function(){var t,s=e(this);s.data("ui-tooltip-open")&&(t=e.Event("blur"),t.target=t.currentTarget=this,i.close(t,!0)),s.attr("title")&&(s.uniqueId(),i.parents[this.id]={element:this,title:s.attr("title")},s.attr("title",""))}),this._registerCloseHandlers(t,s),this._updateContent(s,t))},_updateContent:function(e,t){var i,s=this.options.content,n=this,a=t?t.type:null;return"string"==typeof s?this._open(t,e,s):(i=s.call(e[0],function(i){n._delay(function(){e.data("ui-tooltip-open")&&(t&&(t.type=a),this._open(t,e,i))})}),i&&this._open(t,e,i),void 0)},_open:function(t,i,s){function n(e){l.of=e,o.is(":hidden")||o.position(l)}var a,o,r,h,l=e.extend({},this.options.position);if(s){if(a=this._find(i))return a.tooltip.find(".ui-tooltip-content").html(s),void 0;i.is("[title]")&&(t&&"mouseover"===t.type?i.attr("title",""):i.removeAttr("title")),a=this._tooltip(i),o=a.tooltip,this._addDescribedBy(i,o.attr("id")),o.find(".ui-tooltip-content").html(s),this.liveRegion.children().hide(),s.clone?(h=s.clone(),h.removeAttr("id").find("[id]").removeAttr("id")):h=s,e("<div>").html(h).appendTo(this.liveRegion),this.options.track&&t&&/^mouse/.test(t.type)?(this._on(this.document,{mousemove:n}),n(t)):o.position(e.extend({of:i},this.options.position)),o.hide(),this._show(o,this.options.show),this.options.show&&this.options.show.delay&&(r=this.delayedShow=setInterval(function(){o.is(":visible")&&(n(l.of),clearInterval(r))},e.fx.interval)),this._trigger("open",t,{tooltip:o})}},_registerCloseHandlers:function(t,i){var s={keyup:function(t){if(t.keyCode===e.ui.keyCode.ESCAPE){var s=e.Event(t);s.currentTarget=i[0],this.close(s,!0)}}};i[0]!==this.element[0]&&(s.remove=function(){this._removeTooltip(this._find(i).tooltip)}),t&&"mouseover"!==t.type||(s.mouseleave="close"),t&&"focusin"!==t.type||(s.focusout="close"),this._on(!0,i,s)},close:function(t){var i,s=this,n=e(t?t.currentTarget:this.element),a=this._find(n);return a?(i=a.tooltip,a.closing||(clearInterval(this.delayedShow),n.data("ui-tooltip-title")&&!n.attr("title")&&n.attr("title",n.data("ui-tooltip-title")),this._removeDescribedBy(n),a.hiding=!0,i.stop(!0),this._hide(i,this.options.hide,function(){s._removeTooltip(e(this))}),n.removeData("ui-tooltip-open"),this._off(n,"mouseleave focusout keyup"),n[0]!==this.element[0]&&this._off(n,"remove"),this._off(this.document,"mousemove"),t&&"mouseleave"===t.type&&e.each(this.parents,function(t,i){e(i.element).attr("title",i.title),delete s.parents[t]}),a.closing=!0,this._trigger("close",t,{tooltip:i}),a.hiding||(a.closing=!1)),void 0):(n.removeData("ui-tooltip-open"),void 0)},_tooltip:function(t){var i=e("<div>").attr("role","tooltip").addClass("ui-tooltip ui-widget ui-corner-all ui-widget-content "+(this.options.tooltipClass||"")),s=i.uniqueId().attr("id");return e("<div>").addClass("ui-tooltip-content").appendTo(i),i.appendTo(this.document[0].body),this.tooltips[s]={element:t,tooltip:i}},_find:function(e){var t=e.data("ui-tooltip-id");return t?this.tooltips[t]:null},_removeTooltip:function(e){e.remove(),delete this.tooltips[e.attr("id")]},_destroy:function(){var t=this;e.each(this.tooltips,function(i,s){var n=e.Event("blur"),a=s.element;n.target=n.currentTarget=a[0],t.close(n,!0),e("#"+i).remove(),a.data("ui-tooltip-title")&&(a.attr("title")||a.attr("title",a.data("ui-tooltip-title")),a.removeData("ui-tooltip-title"))}),this.liveRegion.remove()}});var c="ui-effects-",p=e;e.effects={effect:{}},function(e,t){function i(e,t,i){var s=d[t.type]||{};return null==e?i||!t.def?null:t.def:(e=s.floor?~~e:parseFloat(e),isNaN(e)?t.def:s.mod?(e+s.mod)%s.mod:0>e?0:e>s.max?s.max:e)}function s(i){var s=l(),n=s._rgba=[];return i=i.toLowerCase(),f(h,function(e,a){var o,r=a.re.exec(i),h=r&&a.parse(r),l=a.space||"rgba";return h?(o=s[l](h),s[u[l].cache]=o[u[l].cache],n=s._rgba=o._rgba,!1):t}),n.length?("0,0,0,0"===n.join()&&e.extend(n,a.transparent),s):a[i]}function n(e,t,i){return i=(i+1)%1,1>6*i?e+6*(t-e)*i:1>2*i?t:2>3*i?e+6*(t-e)*(2/3-i):e}var a,o="backgroundColor borderBottomColor borderLeftColor borderRightColor borderTopColor color columnRuleColor outlineColor textDecorationColor textEmphasisColor",r=/^([\-+])=\s*(\d+\.?\d*)/,h=[{re:/rgba?\(\s*(\d{1,3})\s*,\s*(\d{1,3})\s*,\s*(\d{1,3})\s*(?:,\s*(\d?(?:\.\d+)?)\s*)?\)/,parse:function(e){return[e[1],e[2],e[3],e[4]]}},{re:/rgba?\(\s*(\d+(?:\.\d+)?)\%\s*,\s*(\d+(?:\.\d+)?)\%\s*,\s*(\d+(?:\.\d+)?)\%\s*(?:,\s*(\d?(?:\.\d+)?)\s*)?\)/,parse:function(e){return[2.55*e[1],2.55*e[2],2.55*e[3],e[4]]}},{re:/#([a-f0-9]{2})([a-f0-9]{2})([a-f0-9]{2})/,parse:function(e){return[parseInt(e[1],16),parseInt(e[2],16),parseInt(e[3],16)]}},{re:/#([a-f0-9])([a-f0-9])([a-f0-9])/,parse:function(e){return[parseInt(e[1]+e[1],16),parseInt(e[2]+e[2],16),parseInt(e[3]+e[3],16)]}},{re:/hsla?\(\s*(\d+(?:\.\d+)?)\s*,\s*(\d+(?:\.\d+)?)\%\s*,\s*(\d+(?:\.\d+)?)\%\s*(?:,\s*(\d?(?:\.\d+)?)\s*)?\)/,space:"hsla",parse:function(e){return[e[1],e[2]/100,e[3]/100,e[4]]}}],l=e.Color=function(t,i,s,n){return new e.Color.fn.parse(t,i,s,n)},u={rgba:{props:{red:{idx:0,type:"byte"},green:{idx:1,type:"byte"},blue:{idx:2,type:"byte"}}},hsla:{props:{hue:{idx:0,type:"degrees"},saturation:{idx:1,type:"percent"},lightness:{idx:2,type:"percent"}}}},d={"byte":{floor:!0,max:255},percent:{max:1},degrees:{mod:360,floor:!0}},c=l.support={},p=e("<p>")[0],f=e.each;p.style.cssText="background-color:rgba(1,1,1,.5)",c.rgba=p.style.backgroundColor.indexOf("rgba")>-1,f(u,function(e,t){t.cache="_"+e,t.props.alpha={idx:3,type:"percent",def:1}}),l.fn=e.extend(l.prototype,{parse:function(n,o,r,h){if(n===t)return this._rgba=[null,null,null,null],this;(n.jquery||n.nodeType)&&(n=e(n).css(o),o=t);var d=this,c=e.type(n),p=this._rgba=[];return o!==t&&(n=[n,o,r,h],c="array"),"string"===c?this.parse(s(n)||a._default):"array"===c?(f(u.rgba.props,function(e,t){p[t.idx]=i(n[t.idx],t)}),this):"object"===c?(n instanceof l?f(u,function(e,t){n[t.cache]&&(d[t.cache]=n[t.cache].slice())}):f(u,function(t,s){var a=s.cache;f(s.props,function(e,t){if(!d[a]&&s.to){if("alpha"===e||null==n[e])return;d[a]=s.to(d._rgba)}d[a][t.idx]=i(n[e],t,!0)}),d[a]&&0>e.inArray(null,d[a].slice(0,3))&&(d[a][3]=1,s.from&&(d._rgba=s.from(d[a])))}),this):t},is:function(e){var i=l(e),s=!0,n=this;return f(u,function(e,a){var o,r=i[a.cache];return r&&(o=n[a.cache]||a.to&&a.to(n._rgba)||[],f(a.props,function(e,i){return null!=r[i.idx]?s=r[i.idx]===o[i.idx]:t})),s}),s},_space:function(){var e=[],t=this;return f(u,function(i,s){t[s.cache]&&e.push(i)}),e.pop()},transition:function(e,t){var s=l(e),n=s._space(),a=u[n],o=0===this.alpha()?l("transparent"):this,r=o[a.cache]||a.to(o._rgba),h=r.slice();return s=s[a.cache],f(a.props,function(e,n){var a=n.idx,o=r[a],l=s[a],u=d[n.type]||{};null!==l&&(null===o?h[a]=l:(u.mod&&(l-o>u.mod/2?o+=u.mod:o-l>u.mod/2&&(o-=u.mod)),h[a]=i((l-o)*t+o,n)))}),this[n](h)},blend:function(t){if(1===this._rgba[3])return this;var i=this._rgba.slice(),s=i.pop(),n=l(t)._rgba;return l(e.map(i,function(e,t){return(1-s)*n[t]+s*e}))},toRgbaString:function(){var t="rgba(",i=e.map(this._rgba,function(e,t){return null==e?t>2?1:0:e});return 1===i[3]&&(i.pop(),t="rgb("),t+i.join()+")"},toHslaString:function(){var t="hsla(",i=e.map(this.hsla(),function(e,t){return null==e&&(e=t>2?1:0),t&&3>t&&(e=Math.round(100*e)+"%"),e});return 1===i[3]&&(i.pop(),t="hsl("),t+i.join()+")"},toHexString:function(t){var i=this._rgba.slice(),s=i.pop();return t&&i.push(~~(255*s)),"#"+e.map(i,function(e){return e=(e||0).toString(16),1===e.length?"0"+e:e}).join("")},toString:function(){return 0===this._rgba[3]?"transparent":this.toRgbaString()}}),l.fn.parse.prototype=l.fn,u.hsla.to=function(e){if(null==e[0]||null==e[1]||null==e[2])return[null,null,null,e[3]];var t,i,s=e[0]/255,n=e[1]/255,a=e[2]/255,o=e[3],r=Math.max(s,n,a),h=Math.min(s,n,a),l=r-h,u=r+h,d=.5*u;return t=h===r?0:s===r?60*(n-a)/l+360:n===r?60*(a-s)/l+120:60*(s-n)/l+240,i=0===l?0:.5>=d?l/u:l/(2-u),[Math.round(t)%360,i,d,null==o?1:o]},u.hsla.from=function(e){if(null==e[0]||null==e[1]||null==e[2])return[null,null,null,e[3]];var t=e[0]/360,i=e[1],s=e[2],a=e[3],o=.5>=s?s*(1+i):s+i-s*i,r=2*s-o;return[Math.round(255*n(r,o,t+1/3)),Math.round(255*n(r,o,t)),Math.round(255*n(r,o,t-1/3)),a]},f(u,function(s,n){var a=n.props,o=n.cache,h=n.to,u=n.from;l.fn[s]=function(s){if(h&&!this[o]&&(this[o]=h(this._rgba)),s===t)return this[o].slice();var n,r=e.type(s),d="array"===r||"object"===r?s:arguments,c=this[o].slice();return f(a,function(e,t){var s=d["object"===r?e:t.idx];null==s&&(s=c[t.idx]),c[t.idx]=i(s,t)}),u?(n=l(u(c)),n[o]=c,n):l(c)},f(a,function(t,i){l.fn[t]||(l.fn[t]=function(n){var a,o=e.type(n),h="alpha"===t?this._hsla?"hsla":"rgba":s,l=this[h](),u=l[i.idx];return"undefined"===o?u:("function"===o&&(n=n.call(this,u),o=e.type(n)),null==n&&i.empty?this:("string"===o&&(a=r.exec(n),a&&(n=u+parseFloat(a[2])*("+"===a[1]?1:-1))),l[i.idx]=n,this[h](l)))})})}),l.hook=function(t){var i=t.split(" ");f(i,function(t,i){e.cssHooks[i]={set:function(t,n){var a,o,r="";if("transparent"!==n&&("string"!==e.type(n)||(a=s(n)))){if(n=l(a||n),!c.rgba&&1!==n._rgba[3]){for(o="backgroundColor"===i?t.parentNode:t;(""===r||"transparent"===r)&&o&&o.style;)try{r=e.css(o,"backgroundColor"),o=o.parentNode}catch(h){}n=n.blend(r&&"transparent"!==r?r:"_default")}n=n.toRgbaString()}try{t.style[i]=n}catch(h){}}},e.fx.step[i]=function(t){t.colorInit||(t.start=l(t.elem,i),t.end=l(t.end),t.colorInit=!0),e.cssHooks[i].set(t.elem,t.start.transition(t.end,t.pos))}})},l.hook(o),e.cssHooks.borderColor={expand:function(e){var t={};return f(["Top","Right","Bottom","Left"],function(i,s){t["border"+s+"Color"]=e}),t}},a=e.Color.names={aqua:"#00ffff",black:"#000000",blue:"#0000ff",fuchsia:"#ff00ff",gray:"#808080",green:"#008000",lime:"#00ff00",maroon:"#800000",navy:"#000080",olive:"#808000",purple:"#800080",red:"#ff0000",silver:"#c0c0c0",teal:"#008080",white:"#ffffff",yellow:"#ffff00",transparent:[null,null,null,0],_default:"#ffffff"}}(p),function(){function t(t){var i,s,n=t.ownerDocument.defaultView?t.ownerDocument.defaultView.getComputedStyle(t,null):t.currentStyle,a={};if(n&&n.length&&n[0]&&n[n[0]])for(s=n.length;s--;)i=n[s],"string"==typeof n[i]&&(a[e.camelCase(i)]=n[i]);else for(i in n)"string"==typeof n[i]&&(a[i]=n[i]);return a}function i(t,i){var s,a,o={};for(s in i)a=i[s],t[s]!==a&&(n[s]||(e.fx.step[s]||!isNaN(parseFloat(a)))&&(o[s]=a));return o}var s=["add","remove","toggle"],n={border:1,borderBottom:1,borderColor:1,borderLeft:1,borderRight:1,borderTop:1,borderWidth:1,margin:1,padding:1};e.each(["borderLeftStyle","borderRightStyle","borderBottomStyle","borderTopStyle"],function(t,i){e.fx.step[i]=function(e){("none"!==e.end&&!e.setAttr||1===e.pos&&!e.setAttr)&&(p.style(e.elem,i,e.end),e.setAttr=!0)}}),e.fn.addBack||(e.fn.addBack=function(e){return this.add(null==e?this.prevObject:this.prevObject.filter(e))}),e.effects.animateClass=function(n,a,o,r){var h=e.speed(a,o,r);return this.queue(function(){var a,o=e(this),r=o.attr("class")||"",l=h.children?o.find("*").addBack():o;l=l.map(function(){var i=e(this);return{el:i,start:t(this)}}),a=function(){e.each(s,function(e,t){n[t]&&o[t+"Class"](n[t])})},a(),l=l.map(function(){return this.end=t(this.el[0]),this.diff=i(this.start,this.end),this}),o.attr("class",r),l=l.map(function(){var t=this,i=e.Deferred(),s=e.extend({},h,{queue:!1,complete:function(){i.resolve(t)}});return this.el.animate(this.diff,s),i.promise()}),e.when.apply(e,l.get()).done(function(){a(),e.each(arguments,function(){var t=this.el;e.each(this.diff,function(e){t.css(e,"")})}),h.complete.call(o[0])})})},e.fn.extend({addClass:function(t){return function(i,s,n,a){return s?e.effects.animateClass.call(this,{add:i},s,n,a):t.apply(this,arguments)}}(e.fn.addClass),removeClass:function(t){return function(i,s,n,a){return arguments.length>1?e.effects.animateClass.call(this,{remove:i},s,n,a):t.apply(this,arguments)}}(e.fn.removeClass),toggleClass:function(t){return function(i,s,n,a,o){return"boolean"==typeof s||void 0===s?n?e.effects.animateClass.call(this,s?{add:i}:{remove:i},n,a,o):t.apply(this,arguments):e.effects.animateClass.call(this,{toggle:i},s,n,a)}}(e.fn.toggleClass),switchClass:function(t,i,s,n,a){return e.effects.animateClass.call(this,{add:i,remove:t},s,n,a)}})}(),function(){function t(t,i,s,n){return e.isPlainObject(t)&&(i=t,t=t.effect),t={effect:t},null==i&&(i={}),e.isFunction(i)&&(n=i,s=null,i={}),("number"==typeof i||e.fx.speeds[i])&&(n=s,s=i,i={}),e.isFunction(s)&&(n=s,s=null),i&&e.extend(t,i),s=s||i.duration,t.duration=e.fx.off?0:"number"==typeof s?s:s in e.fx.speeds?e.fx.speeds[s]:e.fx.speeds._default,t.complete=n||i.complete,t}function i(t){return!t||"number"==typeof t||e.fx.speeds[t]?!0:"string"!=typeof t||e.effects.effect[t]?e.isFunction(t)?!0:"object"!=typeof t||t.effect?!1:!0:!0}e.extend(e.effects,{version:"1.11.4",save:function(e,t){for(var i=0;t.length>i;i++)null!==t[i]&&e.data(c+t[i],e[0].style[t[i]])},restore:function(e,t){var i,s;for(s=0;t.length>s;s++)null!==t[s]&&(i=e.data(c+t[s]),void 0===i&&(i=""),e.css(t[s],i))},setMode:function(e,t){return"toggle"===t&&(t=e.is(":hidden")?"show":"hide"),t},getBaseline:function(e,t){var i,s;switch(e[0]){case"top":i=0;break;case"middle":i=.5;break;case"bottom":i=1;break;default:i=e[0]/t.height}switch(e[1]){case"left":s=0;break;case"center":s=.5;break;case"right":s=1;break;default:s=e[1]/t.width}return{x:s,y:i}},createWrapper:function(t){if(t.parent().is(".ui-effects-wrapper"))return t.parent();var i={width:t.outerWidth(!0),height:t.outerHeight(!0),"float":t.css("float")},s=e("<div></div>").addClass("ui-effects-wrapper").css({fontSize:"100%",background:"transparent",border:"none",margin:0,padding:0}),n={width:t.width(),height:t.height()},a=document.activeElement;try{a.id}catch(o){a=document.body}return t.wrap(s),(t[0]===a||e.contains(t[0],a))&&e(a).focus(),s=t.parent(),"static"===t.css("position")?(s.css({position:"relative"}),t.css({position:"relative"})):(e.extend(i,{position:t.css("position"),zIndex:t.css("z-index")}),e.each(["top","left","bottom","right"],function(e,s){i[s]=t.css(s),isNaN(parseInt(i[s],10))&&(i[s]="auto")}),t.css({position:"relative",top:0,left:0,right:"auto",bottom:"auto"})),t.css(n),s.css(i).show()},removeWrapper:function(t){var i=document.activeElement;return t.parent().is(".ui-effects-wrapper")&&(t.parent().replaceWith(t),(t[0]===i||e.contains(t[0],i))&&e(i).focus()),t},setTransition:function(t,i,s,n){return n=n||{},e.each(i,function(e,i){var a=t.cssUnit(i);a[0]>0&&(n[i]=a[0]*s+a[1])}),n}}),e.fn.extend({effect:function(){function i(t){function i(){e.isFunction(a)&&a.call(n[0]),e.isFunction(t)&&t()}var n=e(this),a=s.complete,r=s.mode;(n.is(":hidden")?"hide"===r:"show"===r)?(n[r](),i()):o.call(n[0],s,i)}var s=t.apply(this,arguments),n=s.mode,a=s.queue,o=e.effects.effect[s.effect];return e.fx.off||!o?n?this[n](s.duration,s.complete):this.each(function(){s.complete&&s.complete.call(this)}):a===!1?this.each(i):this.queue(a||"fx",i)},show:function(e){return function(s){if(i(s))return e.apply(this,arguments);var n=t.apply(this,arguments);return n.mode="show",this.effect.call(this,n)}}(e.fn.show),hide:function(e){return function(s){if(i(s))return e.apply(this,arguments);var n=t.apply(this,arguments);return n.mode="hide",this.effect.call(this,n)}}(e.fn.hide),toggle:function(e){return function(s){if(i(s)||"boolean"==typeof s)return e.apply(this,arguments);var n=t.apply(this,arguments);return n.mode="toggle",this.effect.call(this,n)}}(e.fn.toggle),cssUnit:function(t){var i=this.css(t),s=[];return e.each(["em","px","%","pt"],function(e,t){i.indexOf(t)>0&&(s=[parseFloat(i),t])}),s}})}(),function(){var t={};e.each(["Quad","Cubic","Quart","Quint","Expo"],function(e,i){t[i]=function(t){return Math.pow(t,e+2)}}),e.extend(t,{Sine:function(e){return 1-Math.cos(e*Math.PI/2)},Circ:function(e){return 1-Math.sqrt(1-e*e)},Elastic:function(e){return 0===e||1===e?e:-Math.pow(2,8*(e-1))*Math.sin((80*(e-1)-7.5)*Math.PI/15)},Back:function(e){return e*e*(3*e-2)},Bounce:function(e){for(var t,i=4;((t=Math.pow(2,--i))-1)/11>e;);return 1/Math.pow(4,3-i)-7.5625*Math.pow((3*t-2)/22-e,2)}}),e.each(t,function(t,i){e.easing["easeIn"+t]=i,e.easing["easeOut"+t]=function(e){return 1-i(1-e)},e.easing["easeInOut"+t]=function(e){return.5>e?i(2*e)/2:1-i(-2*e+2)/2}})}(),e.effects,e.effects.effect.blind=function(t,i){var s,n,a,o=e(this),r=/up|down|vertical/,h=/up|left|vertical|horizontal/,l=["position","top","bottom","left","right","height","width"],u=e.effects.setMode(o,t.mode||"hide"),d=t.direction||"up",c=r.test(d),p=c?"height":"width",f=c?"top":"left",m=h.test(d),g={},v="show"===u;o.parent().is(".ui-effects-wrapper")?e.effects.save(o.parent(),l):e.effects.save(o,l),o.show(),s=e.effects.createWrapper(o).css({overflow:"hidden"}),n=s[p](),a=parseFloat(s.css(f))||0,g[p]=v?n:0,m||(o.css(c?"bottom":"right",0).css(c?"top":"left","auto").css({position:"absolute"}),g[f]=v?a:n+a),v&&(s.css(p,0),m||s.css(f,a+n)),s.animate(g,{duration:t.duration,easing:t.easing,queue:!1,complete:function(){"hide"===u&&o.hide(),e.effects.restore(o,l),e.effects.removeWrapper(o),i()
}})},e.effects.effect.bounce=function(t,i){var s,n,a,o=e(this),r=["position","top","bottom","left","right","height","width"],h=e.effects.setMode(o,t.mode||"effect"),l="hide"===h,u="show"===h,d=t.direction||"up",c=t.distance,p=t.times||5,f=2*p+(u||l?1:0),m=t.duration/f,g=t.easing,v="up"===d||"down"===d?"top":"left",y="up"===d||"left"===d,b=o.queue(),_=b.length;for((u||l)&&r.push("opacity"),e.effects.save(o,r),o.show(),e.effects.createWrapper(o),c||(c=o["top"===v?"outerHeight":"outerWidth"]()/3),u&&(a={opacity:1},a[v]=0,o.css("opacity",0).css(v,y?2*-c:2*c).animate(a,m,g)),l&&(c/=Math.pow(2,p-1)),a={},a[v]=0,s=0;p>s;s++)n={},n[v]=(y?"-=":"+=")+c,o.animate(n,m,g).animate(a,m,g),c=l?2*c:c/2;l&&(n={opacity:0},n[v]=(y?"-=":"+=")+c,o.animate(n,m,g)),o.queue(function(){l&&o.hide(),e.effects.restore(o,r),e.effects.removeWrapper(o),i()}),_>1&&b.splice.apply(b,[1,0].concat(b.splice(_,f+1))),o.dequeue()},e.effects.effect.clip=function(t,i){var s,n,a,o=e(this),r=["position","top","bottom","left","right","height","width"],h=e.effects.setMode(o,t.mode||"hide"),l="show"===h,u=t.direction||"vertical",d="vertical"===u,c=d?"height":"width",p=d?"top":"left",f={};e.effects.save(o,r),o.show(),s=e.effects.createWrapper(o).css({overflow:"hidden"}),n="IMG"===o[0].tagName?s:o,a=n[c](),l&&(n.css(c,0),n.css(p,a/2)),f[c]=l?a:0,f[p]=l?0:a/2,n.animate(f,{queue:!1,duration:t.duration,easing:t.easing,complete:function(){l||o.hide(),e.effects.restore(o,r),e.effects.removeWrapper(o),i()}})},e.effects.effect.drop=function(t,i){var s,n=e(this),a=["position","top","bottom","left","right","opacity","height","width"],o=e.effects.setMode(n,t.mode||"hide"),r="show"===o,h=t.direction||"left",l="up"===h||"down"===h?"top":"left",u="up"===h||"left"===h?"pos":"neg",d={opacity:r?1:0};e.effects.save(n,a),n.show(),e.effects.createWrapper(n),s=t.distance||n["top"===l?"outerHeight":"outerWidth"](!0)/2,r&&n.css("opacity",0).css(l,"pos"===u?-s:s),d[l]=(r?"pos"===u?"+=":"-=":"pos"===u?"-=":"+=")+s,n.animate(d,{queue:!1,duration:t.duration,easing:t.easing,complete:function(){"hide"===o&&n.hide(),e.effects.restore(n,a),e.effects.removeWrapper(n),i()}})},e.effects.effect.explode=function(t,i){function s(){b.push(this),b.length===d*c&&n()}function n(){p.css({visibility:"visible"}),e(b).remove(),m||p.hide(),i()}var a,o,r,h,l,u,d=t.pieces?Math.round(Math.sqrt(t.pieces)):3,c=d,p=e(this),f=e.effects.setMode(p,t.mode||"hide"),m="show"===f,g=p.show().css("visibility","hidden").offset(),v=Math.ceil(p.outerWidth()/c),y=Math.ceil(p.outerHeight()/d),b=[];for(a=0;d>a;a++)for(h=g.top+a*y,u=a-(d-1)/2,o=0;c>o;o++)r=g.left+o*v,l=o-(c-1)/2,p.clone().appendTo("body").wrap("<div></div>").css({position:"absolute",visibility:"visible",left:-o*v,top:-a*y}).parent().addClass("ui-effects-explode").css({position:"absolute",overflow:"hidden",width:v,height:y,left:r+(m?l*v:0),top:h+(m?u*y:0),opacity:m?0:1}).animate({left:r+(m?0:l*v),top:h+(m?0:u*y),opacity:m?1:0},t.duration||500,t.easing,s)},e.effects.effect.fade=function(t,i){var s=e(this),n=e.effects.setMode(s,t.mode||"toggle");s.animate({opacity:n},{queue:!1,duration:t.duration,easing:t.easing,complete:i})},e.effects.effect.fold=function(t,i){var s,n,a=e(this),o=["position","top","bottom","left","right","height","width"],r=e.effects.setMode(a,t.mode||"hide"),h="show"===r,l="hide"===r,u=t.size||15,d=/([0-9]+)%/.exec(u),c=!!t.horizFirst,p=h!==c,f=p?["width","height"]:["height","width"],m=t.duration/2,g={},v={};e.effects.save(a,o),a.show(),s=e.effects.createWrapper(a).css({overflow:"hidden"}),n=p?[s.width(),s.height()]:[s.height(),s.width()],d&&(u=parseInt(d[1],10)/100*n[l?0:1]),h&&s.css(c?{height:0,width:u}:{height:u,width:0}),g[f[0]]=h?n[0]:u,v[f[1]]=h?n[1]:0,s.animate(g,m,t.easing).animate(v,m,t.easing,function(){l&&a.hide(),e.effects.restore(a,o),e.effects.removeWrapper(a),i()})},e.effects.effect.highlight=function(t,i){var s=e(this),n=["backgroundImage","backgroundColor","opacity"],a=e.effects.setMode(s,t.mode||"show"),o={backgroundColor:s.css("backgroundColor")};"hide"===a&&(o.opacity=0),e.effects.save(s,n),s.show().css({backgroundImage:"none",backgroundColor:t.color||"#ffff99"}).animate(o,{queue:!1,duration:t.duration,easing:t.easing,complete:function(){"hide"===a&&s.hide(),e.effects.restore(s,n),i()}})},e.effects.effect.size=function(t,i){var s,n,a,o=e(this),r=["position","top","bottom","left","right","width","height","overflow","opacity"],h=["position","top","bottom","left","right","overflow","opacity"],l=["width","height","overflow"],u=["fontSize"],d=["borderTopWidth","borderBottomWidth","paddingTop","paddingBottom"],c=["borderLeftWidth","borderRightWidth","paddingLeft","paddingRight"],p=e.effects.setMode(o,t.mode||"effect"),f=t.restore||"effect"!==p,m=t.scale||"both",g=t.origin||["middle","center"],v=o.css("position"),y=f?r:h,b={height:0,width:0,outerHeight:0,outerWidth:0};"show"===p&&o.show(),s={height:o.height(),width:o.width(),outerHeight:o.outerHeight(),outerWidth:o.outerWidth()},"toggle"===t.mode&&"show"===p?(o.from=t.to||b,o.to=t.from||s):(o.from=t.from||("show"===p?b:s),o.to=t.to||("hide"===p?b:s)),a={from:{y:o.from.height/s.height,x:o.from.width/s.width},to:{y:o.to.height/s.height,x:o.to.width/s.width}},("box"===m||"both"===m)&&(a.from.y!==a.to.y&&(y=y.concat(d),o.from=e.effects.setTransition(o,d,a.from.y,o.from),o.to=e.effects.setTransition(o,d,a.to.y,o.to)),a.from.x!==a.to.x&&(y=y.concat(c),o.from=e.effects.setTransition(o,c,a.from.x,o.from),o.to=e.effects.setTransition(o,c,a.to.x,o.to))),("content"===m||"both"===m)&&a.from.y!==a.to.y&&(y=y.concat(u).concat(l),o.from=e.effects.setTransition(o,u,a.from.y,o.from),o.to=e.effects.setTransition(o,u,a.to.y,o.to)),e.effects.save(o,y),o.show(),e.effects.createWrapper(o),o.css("overflow","hidden").css(o.from),g&&(n=e.effects.getBaseline(g,s),o.from.top=(s.outerHeight-o.outerHeight())*n.y,o.from.left=(s.outerWidth-o.outerWidth())*n.x,o.to.top=(s.outerHeight-o.to.outerHeight)*n.y,o.to.left=(s.outerWidth-o.to.outerWidth)*n.x),o.css(o.from),("content"===m||"both"===m)&&(d=d.concat(["marginTop","marginBottom"]).concat(u),c=c.concat(["marginLeft","marginRight"]),l=r.concat(d).concat(c),o.find("*[width]").each(function(){var i=e(this),s={height:i.height(),width:i.width(),outerHeight:i.outerHeight(),outerWidth:i.outerWidth()};f&&e.effects.save(i,l),i.from={height:s.height*a.from.y,width:s.width*a.from.x,outerHeight:s.outerHeight*a.from.y,outerWidth:s.outerWidth*a.from.x},i.to={height:s.height*a.to.y,width:s.width*a.to.x,outerHeight:s.height*a.to.y,outerWidth:s.width*a.to.x},a.from.y!==a.to.y&&(i.from=e.effects.setTransition(i,d,a.from.y,i.from),i.to=e.effects.setTransition(i,d,a.to.y,i.to)),a.from.x!==a.to.x&&(i.from=e.effects.setTransition(i,c,a.from.x,i.from),i.to=e.effects.setTransition(i,c,a.to.x,i.to)),i.css(i.from),i.animate(i.to,t.duration,t.easing,function(){f&&e.effects.restore(i,l)})})),o.animate(o.to,{queue:!1,duration:t.duration,easing:t.easing,complete:function(){0===o.to.opacity&&o.css("opacity",o.from.opacity),"hide"===p&&o.hide(),e.effects.restore(o,y),f||("static"===v?o.css({position:"relative",top:o.to.top,left:o.to.left}):e.each(["top","left"],function(e,t){o.css(t,function(t,i){var s=parseInt(i,10),n=e?o.to.left:o.to.top;return"auto"===i?n+"px":s+n+"px"})})),e.effects.removeWrapper(o),i()}})},e.effects.effect.scale=function(t,i){var s=e(this),n=e.extend(!0,{},t),a=e.effects.setMode(s,t.mode||"effect"),o=parseInt(t.percent,10)||(0===parseInt(t.percent,10)?0:"hide"===a?0:100),r=t.direction||"both",h=t.origin,l={height:s.height(),width:s.width(),outerHeight:s.outerHeight(),outerWidth:s.outerWidth()},u={y:"horizontal"!==r?o/100:1,x:"vertical"!==r?o/100:1};n.effect="size",n.queue=!1,n.complete=i,"effect"!==a&&(n.origin=h||["middle","center"],n.restore=!0),n.from=t.from||("show"===a?{height:0,width:0,outerHeight:0,outerWidth:0}:l),n.to={height:l.height*u.y,width:l.width*u.x,outerHeight:l.outerHeight*u.y,outerWidth:l.outerWidth*u.x},n.fade&&("show"===a&&(n.from.opacity=0,n.to.opacity=1),"hide"===a&&(n.from.opacity=1,n.to.opacity=0)),s.effect(n)},e.effects.effect.puff=function(t,i){var s=e(this),n=e.effects.setMode(s,t.mode||"hide"),a="hide"===n,o=parseInt(t.percent,10)||150,r=o/100,h={height:s.height(),width:s.width(),outerHeight:s.outerHeight(),outerWidth:s.outerWidth()};e.extend(t,{effect:"scale",queue:!1,fade:!0,mode:n,complete:i,percent:a?o:100,from:a?h:{height:h.height*r,width:h.width*r,outerHeight:h.outerHeight*r,outerWidth:h.outerWidth*r}}),s.effect(t)},e.effects.effect.pulsate=function(t,i){var s,n=e(this),a=e.effects.setMode(n,t.mode||"show"),o="show"===a,r="hide"===a,h=o||"hide"===a,l=2*(t.times||5)+(h?1:0),u=t.duration/l,d=0,c=n.queue(),p=c.length;for((o||!n.is(":visible"))&&(n.css("opacity",0).show(),d=1),s=1;l>s;s++)n.animate({opacity:d},u,t.easing),d=1-d;n.animate({opacity:d},u,t.easing),n.queue(function(){r&&n.hide(),i()}),p>1&&c.splice.apply(c,[1,0].concat(c.splice(p,l+1))),n.dequeue()},e.effects.effect.shake=function(t,i){var s,n=e(this),a=["position","top","bottom","left","right","height","width"],o=e.effects.setMode(n,t.mode||"effect"),r=t.direction||"left",h=t.distance||20,l=t.times||3,u=2*l+1,d=Math.round(t.duration/u),c="up"===r||"down"===r?"top":"left",p="up"===r||"left"===r,f={},m={},g={},v=n.queue(),y=v.length;for(e.effects.save(n,a),n.show(),e.effects.createWrapper(n),f[c]=(p?"-=":"+=")+h,m[c]=(p?"+=":"-=")+2*h,g[c]=(p?"-=":"+=")+2*h,n.animate(f,d,t.easing),s=1;l>s;s++)n.animate(m,d,t.easing).animate(g,d,t.easing);n.animate(m,d,t.easing).animate(f,d/2,t.easing).queue(function(){"hide"===o&&n.hide(),e.effects.restore(n,a),e.effects.removeWrapper(n),i()}),y>1&&v.splice.apply(v,[1,0].concat(v.splice(y,u+1))),n.dequeue()},e.effects.effect.slide=function(t,i){var s,n=e(this),a=["position","top","bottom","left","right","width","height"],o=e.effects.setMode(n,t.mode||"show"),r="show"===o,h=t.direction||"left",l="up"===h||"down"===h?"top":"left",u="up"===h||"left"===h,d={};e.effects.save(n,a),n.show(),s=t.distance||n["top"===l?"outerHeight":"outerWidth"](!0),e.effects.createWrapper(n).css({overflow:"hidden"}),r&&n.css(l,u?isNaN(s)?"-"+s:-s:s),d[l]=(r?u?"+=":"-=":u?"-=":"+=")+s,n.animate(d,{queue:!1,duration:t.duration,easing:t.easing,complete:function(){"hide"===o&&n.hide(),e.effects.restore(n,a),e.effects.removeWrapper(n),i()}})},e.effects.effect.transfer=function(t,i){var s=e(this),n=e(t.to),a="fixed"===n.css("position"),o=e("body"),r=a?o.scrollTop():0,h=a?o.scrollLeft():0,l=n.offset(),u={top:l.top-r,left:l.left-h,height:n.innerHeight(),width:n.innerWidth()},d=s.offset(),c=e("<div class='ui-effects-transfer'></div>").appendTo(document.body).addClass(t.className).css({top:d.top-r,left:d.left-h,height:s.innerHeight(),width:s.innerWidth(),position:a?"fixed":"absolute"}).animate(u,t.duration,t.easing,function(){c.remove(),i()})}});</script>
<style type="text/css">

.tocify {
width: 20%;
max-height: 90%;
overflow: auto;
margin-left: 2%;
position: fixed;
border: 1px solid #ccc;
border-radius: 6px;
}

.tocify ul, .tocify li {
list-style: none;
margin: 0;
padding: 0;
border: none;
line-height: 30px;
}

.tocify-header {
text-indent: 10px;
}

.tocify-subheader {
text-indent: 20px;
display: none;
}

.tocify-subheader li {
font-size: 12px;
}

.tocify-subheader .tocify-subheader {
text-indent: 30px;
}
.tocify-subheader .tocify-subheader .tocify-subheader {
text-indent: 40px;
}
.tocify-subheader .tocify-subheader .tocify-subheader .tocify-subheader {
text-indent: 50px;
}
.tocify-subheader .tocify-subheader .tocify-subheader .tocify-subheader .tocify-subheader {
text-indent: 60px;
}

.tocify .tocify-item > a, .tocify .nav-list .nav-header {
margin: 0px;
}

.tocify .tocify-item a, .tocify .list-group-item {
padding: 5px;
}
.tocify .nav-pills > li {
float: none;
}


</style>
<script>/* jquery Tocify - v1.9.1 - 2013-10-22
 * http://www.gregfranko.com/jquery.tocify.js/
 * Copyright (c) 2013 Greg Franko; Licensed MIT */

// Immediately-Invoked Function Expression (IIFE) [Ben Alman Blog Post](http://benalman.com/news/2010/11/immediately-invoked-function-expression/) that calls another IIFE that contains all of the plugin logic.  I used this pattern so that anyone viewing this code would not have to scroll to the bottom of the page to view the local parameters that were passed to the main IIFE.
(function(tocify) {

    // ECMAScript 5 Strict Mode: [John Resig Blog Post](http://ejohn.org/blog/ecmascript-5-strict-mode-json-and-more/)
    "use strict";

    // Calls the second IIFE and locally passes in the global jQuery, window, and document objects
    tocify(window.jQuery, window, document);

  }

  // Locally passes in `jQuery`, the `window` object, the `document` object, and an `undefined` variable.  The `jQuery`, `window` and `document` objects are passed in locally, to improve performance, since javascript first searches for a variable match within the local variables set before searching the global variables set.  All of the global variables are also passed in locally to be minifier friendly. `undefined` can be passed in locally, because it is not a reserved word in JavaScript.
  (function($, window, document, undefined) {

    // ECMAScript 5 Strict Mode: [John Resig Blog Post](http://ejohn.org/blog/ecmascript-5-strict-mode-json-and-more/)
    "use strict";

    var tocClassName = "tocify",
      tocClass = "." + tocClassName,
      tocFocusClassName = "tocify-focus",
      tocHoverClassName = "tocify-hover",
      hideTocClassName = "tocify-hide",
      hideTocClass = "." + hideTocClassName,
      headerClassName = "tocify-header",
      headerClass = "." + headerClassName,
      subheaderClassName = "tocify-subheader",
      subheaderClass = "." + subheaderClassName,
      itemClassName = "tocify-item",
      itemClass = "." + itemClassName,
      extendPageClassName = "tocify-extend-page",
      extendPageClass = "." + extendPageClassName;

    // Calling the jQueryUI Widget Factory Method
    $.widget("toc.tocify", {

      //Plugin version
      version: "1.9.1",

      // These options will be used as defaults
      options: {

        // **context**: Accepts String: Any jQuery selector
        // The container element that holds all of the elements used to generate the table of contents
        context: "body",

        // **ignoreSelector**: Accepts String: Any jQuery selector
        // A selector to any element that would be matched by selectors that you wish to be ignored
        ignoreSelector: null,

        // **selectors**: Accepts an Array of Strings: Any jQuery selectors
        // The element's used to generate the table of contents.  The order is very important since it will determine the table of content's nesting structure
        selectors: "h1, h2, h3",

        // **showAndHide**: Accepts a boolean: true or false
        // Used to determine if elements should be shown and hidden
        showAndHide: true,

        // **showEffect**: Accepts String: "none", "fadeIn", "show", or "slideDown"
        // Used to display any of the table of contents nested items
        showEffect: "slideDown",

        // **showEffectSpeed**: Accepts Number (milliseconds) or String: "slow", "medium", or "fast"
        // The time duration of the show animation
        showEffectSpeed: "medium",

        // **hideEffect**: Accepts String: "none", "fadeOut", "hide", or "slideUp"
        // Used to hide any of the table of contents nested items
        hideEffect: "slideUp",

        // **hideEffectSpeed**: Accepts Number (milliseconds) or String: "slow", "medium", or "fast"
        // The time duration of the hide animation
        hideEffectSpeed: "medium",

        // **smoothScroll**: Accepts a boolean: true or false
        // Determines if a jQuery animation should be used to scroll to specific table of contents items on the page
        smoothScroll: true,

        // **smoothScrollSpeed**: Accepts Number (milliseconds) or String: "slow", "medium", or "fast"
        // The time duration of the smoothScroll animation
        smoothScrollSpeed: "medium",

        // **scrollTo**: Accepts Number (pixels)
        // The amount of space between the top of page and the selected table of contents item after the page has been scrolled
        scrollTo: 0,

        // **showAndHideOnScroll**: Accepts a boolean: true or false
        // Determines if table of contents nested items should be shown and hidden while scrolling
        showAndHideOnScroll: true,

        // **highlightOnScroll**: Accepts a boolean: true or false
        // Determines if table of contents nested items should be highlighted (set to a different color) while scrolling
        highlightOnScroll: true,

        // **highlightOffset**: Accepts a number
        // The offset distance in pixels to trigger the next active table of contents item
        highlightOffset: 40,

        // **theme**: Accepts a string: "bootstrap", "jqueryui", or "none"
        // Determines if Twitter Bootstrap, jQueryUI, or Tocify classes should be added to the table of contents
        theme: "bootstrap",

        // **extendPage**: Accepts a boolean: true or false
        // If a user scrolls to the bottom of the page and the page is not tall enough to scroll to the last table of contents item, then the page height is increased
        extendPage: true,

        // **extendPageOffset**: Accepts a number: pixels
        // How close to the bottom of the page a user must scroll before the page is extended
        extendPageOffset: 100,

        // **history**: Accepts a boolean: true or false
        // Adds a hash to the page url to maintain history
        history: true,

        // **scrollHistory**: Accepts a boolean: true or false
        // Adds a hash to the page url, to maintain history, when scrolling to a TOC item
        scrollHistory: false,

        // **hashGenerator**: How the hash value (the anchor segment of the URL, following the
        // # character) will be generated.
        //
        // "compact" (default) - #CompressesEverythingTogether
        // "pretty" - #looks-like-a-nice-url-and-is-easily-readable
        // function(text, element){} - Your own hash generation function that accepts the text as an
        // argument, and returns the hash value.
        hashGenerator: "compact",

        // **highlightDefault**: Accepts a boolean: true or false
        // Set's the first TOC item as active if no other TOC item is active.
        highlightDefault: true

      },

      // _Create
      // -------
      //      Constructs the plugin.  Only called once.
      _create: function() {

        var self = this;

        self.extendPageScroll = true;

        // Internal array that keeps track of all TOC items (Helps to recognize if there are duplicate TOC item strings)
        self.items = [];

        // Generates the HTML for the dynamic table of contents
        self._generateToc();

        // Adds CSS classes to the newly generated table of contents HTML
        self._addCSSClasses();

        self.webkit = (function() {

          for (var prop in window) {

            if (prop) {

              if (prop.toLowerCase().indexOf("webkit") !== -1) {

                return true;

              }

            }

          }

          return false;

        }());

        // Adds jQuery event handlers to the newly generated table of contents
        self._setEventHandlers();

        // Binding to the Window load event to make sure the correct scrollTop is calculated
        $(window).on("load", function() {

          // Sets the active TOC item
          self._setActiveElement(true);

          // Once all animations on the page are complete, this callback function will be called
          $("html, body").promise().done(function() {

            setTimeout(function() {

              self.extendPageScroll = false;

            }, 0);

          });

        });

      },

      // _generateToc
      // ------------
      //      Generates the HTML for the dynamic table of contents
      _generateToc: function() {

        // _Local variables_

        // Stores the plugin context in the self variable
        var self = this,

          // All of the HTML tags found within the context provided (i.e. body) that match the top level jQuery selector above
          firstElem,

          // Instantiated variable that will store the top level newly created unordered list DOM element
          ul,
          ignoreSelector = self.options.ignoreSelector;


        // Determine the element to start the toc with
        // get all the top level selectors
        firstElem = [];
        var selectors = this.options.selectors.replace(/ /g, "").split(",");
        // find the first set that have at least one non-ignored element
        for(var i = 0; i < selectors.length; i++) {
          var foundSelectors = $(this.options.context).find(selectors[i]);
          for (var s = 0; s < foundSelectors.length; s++) {
            if (!$(foundSelectors[s]).is(ignoreSelector)) {
              firstElem = foundSelectors;
              break;
            }
          }
          if (firstElem.length> 0)
            break;
        }

        if (!firstElem.length) {

          self.element.addClass(hideTocClassName);

          return;

        }

        self.element.addClass(tocClassName);

        // Loops through each top level selector
        firstElem.each(function(index) {

          //If the element matches the ignoreSelector then we skip it
          if ($(this).is(ignoreSelector)) {
            return;
          }

          // Creates an unordered list HTML element and adds a dynamic ID and standard class name
          ul = $("<ul/>", {
            "id": headerClassName + index,
            "class": headerClassName
          }).

          // Appends a top level list item HTML element to the previously created HTML header
          append(self._nestElements($(this), index));

          // Add the created unordered list element to the HTML element calling the plugin
          self.element.append(ul);

          // Finds all of the HTML tags between the header and subheader elements
          $(this).nextUntil(this.nodeName.toLowerCase()).each(function() {

            // If there are no nested subheader elemements
            if ($(this).find(self.options.selectors).length === 0) {

              // Loops through all of the subheader elements
              $(this).filter(self.options.selectors).each(function() {

                //If the element matches the ignoreSelector then we skip it
                if ($(this).is(ignoreSelector)) {
                  return;
                }

                self._appendSubheaders.call(this, self, ul);

              });

            }

            // If there are nested subheader elements
            else {

              // Loops through all of the subheader elements
              $(this).find(self.options.selectors).each(function() {

                //If the element matches the ignoreSelector then we skip it
                if ($(this).is(ignoreSelector)) {
                  return;
                }

                self._appendSubheaders.call(this, self, ul);

              });

            }

          });

        });

      },

      _setActiveElement: function(pageload) {

        var self = this,

          hash = window.location.hash.substring(1),

          elem = self.element.find('li[data-unique="' + hash + '"]');

        if (hash.length) {

          // Removes highlighting from all of the list item's
          self.element.find("." + self.focusClass).removeClass(self.focusClass);

          // Highlights the current list item that was clicked
          elem.addClass(self.focusClass);

          // Triggers the click event on the currently focused TOC item
          elem.click();

        } else {

          // Removes highlighting from all of the list item's
          self.element.find("." + self.focusClass).removeClass(self.focusClass);

          if (!hash.length && pageload && self.options.highlightDefault) {

            // Highlights the first TOC item if no other items are highlighted
            self.element.find(itemClass).first().addClass(self.focusClass);

          }

        }

        return self;

      },

      // _nestElements
      // -------------
      //      Helps create the table of contents list by appending nested list items
      _nestElements: function(self, index) {

        var arr, item, hashValue;

        arr = $.grep(this.items, function(item) {

          return item === self.text();

        });

        // If there is already a duplicate TOC item
        if (arr.length) {

          // Adds the current TOC item text and index (for slight randomization) to the internal array
          this.items.push(self.text() + index);

        }

        // If there not a duplicate TOC item
        else {

          // Adds the current TOC item text to the internal array
          this.items.push(self.text());

        }

        hashValue = this._generateHashValue(arr, self, index);

        // Appends a list item HTML element to the last unordered list HTML element found within the HTML element calling the plugin
        item = $("<li/>", {

          // Sets a common class name to the list item
          "class": itemClassName,

          "data-unique": hashValue

        });

        if (this.options.theme !== "bootstrap3") {

          item.append($("<a/>", {

            "html": self.html()

          }));

        } else {

          item.html(self.html());

        }

        // Adds an HTML anchor tag before the currently traversed HTML element
        self.before($("<div/>", {

          // Sets a name attribute on the anchor tag to the text of the currently traversed HTML element (also making sure that all whitespace is replaced with an underscore)
          "name": hashValue,

          "data-unique": hashValue

        }));

        return item;

      },

      // _generateHashValue
      // ------------------
      //      Generates the hash value that will be used to refer to each item.
      _generateHashValue: function(arr, self, index) {

        var hashValue = "",
          hashGeneratorOption = this.options.hashGenerator;

        if (hashGeneratorOption === "pretty") {

          // prettify the text
          hashValue = self.text().toLowerCase().replace(/\s/g, "-");

          // fix double hyphens
          while (hashValue.indexOf("--") > -1) {
            hashValue = hashValue.replace(/--/g, "-");
          }

          // fix colon-space instances
          while (hashValue.indexOf(":-") > -1) {
            hashValue = hashValue.replace(/:-/g, "-");
          }

        } else if (typeof hashGeneratorOption === "function") {

          // call the function
          hashValue = hashGeneratorOption(self.text(), self);

        } else {

          // compact - the default
          hashValue = self.text().replace(/\s/g, "");

        }

        // add the index if we need to
        if (arr.length) {
          hashValue += "" + index;
        }

        // return the value
        return hashValue;

      },

      // _appendElements
      // ---------------
      //      Helps create the table of contents list by appending subheader elements

      _appendSubheaders: function(self, ul) {

        // The current element index
        var index = $(this).index(self.options.selectors),

          // Finds the previous header DOM element
          previousHeader = $(self.options.selectors).eq(index - 1),

          currentTagName = +$(this).prop("tagName").charAt(1),

          previousTagName = +previousHeader.prop("tagName").charAt(1),

          lastSubheader;

        // If the current header DOM element is smaller than the previous header DOM element or the first subheader
        if (currentTagName < previousTagName) {

          // Selects the last unordered list HTML found within the HTML element calling the plugin
          self.element.find(subheaderClass + "[data-tag=" + currentTagName + "]").last().append(self._nestElements($(this), index));

        }

        // If the current header DOM element is the same type of header(eg. h4) as the previous header DOM element
        else if (currentTagName === previousTagName) {

          ul.find(itemClass).last().after(self._nestElements($(this), index));

        } else {

          // Selects the last unordered list HTML found within the HTML element calling the plugin
          ul.find(itemClass).last().

          // Appends an unorderedList HTML element to the dynamic `unorderedList` variable and sets a common class name
          after($("<ul/>", {

            "class": subheaderClassName,

            "data-tag": currentTagName

          })).next(subheaderClass).

          // Appends a list item HTML element to the last unordered list HTML element found within the HTML element calling the plugin
          append(self._nestElements($(this), index));
        }

      },

      // _setEventHandlers
      // ----------------
      //      Adds jQuery event handlers to the newly generated table of contents
      _setEventHandlers: function() {

        // _Local variables_

        // Stores the plugin context in the self variable
        var self = this,

          // Instantiates a new variable that will be used to hold a specific element's context
          $self,

          // Instantiates a new variable that will be used to determine the smoothScroll animation time duration
          duration;

        // Event delegation that looks for any clicks on list item elements inside of the HTML element calling the plugin
        this.element.on("click.tocify", "li", function(event) {

          if (self.options.history) {

            window.location.hash = $(this).attr("data-unique");

          }

          // Removes highlighting from all of the list item's
          self.element.find("." + self.focusClass).removeClass(self.focusClass);

          // Highlights the current list item that was clicked
          $(this).addClass(self.focusClass);

          // If the showAndHide option is true
          if (self.options.showAndHide) {

            var elem = $('li[data-unique="' + $(this).attr("data-unique") + '"]');

            self._triggerShow(elem);

          }

          self._scrollTo($(this));

        });

        // Mouseenter and Mouseleave event handlers for the list item's within the HTML element calling the plugin
        this.element.find("li").on({

          // Mouseenter event handler
          "mouseenter.tocify": function() {

            // Adds a hover CSS class to the current list item
            $(this).addClass(self.hoverClass);

            // Makes sure the cursor is set to the pointer icon
            $(this).css("cursor", "pointer");

          },

          // Mouseleave event handler
          "mouseleave.tocify": function() {

            if (self.options.theme !== "bootstrap") {

              // Removes the hover CSS class from the current list item
              $(this).removeClass(self.hoverClass);

            }

          }
        });

        // only attach handler if needed (expensive in IE)
        if (self.options.extendPage || self.options.highlightOnScroll || self.options.scrollHistory || self.options.showAndHideOnScroll) {
          // Window scroll event handler
          $(window).on("scroll.tocify", function() {

            // Once all animations on the page are complete, this callback function will be called
            $("html, body").promise().done(function() {

              // Local variables

              // Stores how far the user has scrolled
              var winScrollTop = $(window).scrollTop(),

                // Stores the height of the window
                winHeight = $(window).height(),

                // Stores the height of the document
                docHeight = $(document).height(),

                scrollHeight = $("body")[0].scrollHeight,

                // Instantiates a variable that will be used to hold a selected HTML element
                elem,

                lastElem,

                lastElemOffset,

                currentElem;

              if (self.options.extendPage) {

                // If the user has scrolled to the bottom of the page and the last toc item is not focused
                if ((self.webkit && winScrollTop >= scrollHeight - winHeight - self.options.extendPageOffset) || (!self.webkit && winHeight + winScrollTop > docHeight - self.options.extendPageOffset)) {

                  if (!$(extendPageClass).length) {

                    lastElem = $('div[data-unique="' + $(itemClass).last().attr("data-unique") + '"]');

                    if (!lastElem.length) return;

                    // Gets the top offset of the page header that is linked to the last toc item
                    lastElemOffset = lastElem.offset().top;

                    // Appends a div to the bottom of the page and sets the height to the difference of the window scrollTop and the last element's position top offset
                    $(self.options.context).append($("<div/>", {

                      "class": extendPageClassName,

                      "height": Math.abs(lastElemOffset - winScrollTop) + "px",

                      "data-unique": extendPageClassName

                    }));

                    if (self.extendPageScroll) {

                      currentElem = self.element.find('li.' + self.focusClass);

                      self._scrollTo($('div[data-unique="' + currentElem.attr("data-unique") + '"]'));

                    }

                  }

                }

              }

              // The zero timeout ensures the following code is run after the scroll events
              setTimeout(function() {

                // _Local variables_

                // Stores the distance to the closest anchor
                var closestAnchorDistance = null,

                  // Stores the index of the closest anchor
                  closestAnchorIdx = null,

                  // Keeps a reference to all anchors
                  anchors = $(self.options.context).find("div[data-unique]"),

                  anchorText;

                // Determines the index of the closest anchor
                anchors.each(function(idx) {
                  var distance = Math.abs(($(this).next().length ? $(this).next() : $(this)).offset().top - winScrollTop - self.options.highlightOffset);
                  if (closestAnchorDistance == null || distance < closestAnchorDistance) {
                    closestAnchorDistance = distance;
                    closestAnchorIdx = idx;
                  } else {
                    return false;
                  }
                });

                anchorText = $(anchors[closestAnchorIdx]).attr("data-unique");

                // Stores the list item HTML element that corresponds to the currently traversed anchor tag
                elem = $('li[data-unique="' + anchorText + '"]');

                // If the `highlightOnScroll` option is true and a next element is found
                if (self.options.highlightOnScroll && elem.length) {

                  // Removes highlighting from all of the list item's
                  self.element.find("." + self.focusClass).removeClass(self.focusClass);

                  // Highlights the corresponding list item
                  elem.addClass(self.focusClass);

                }

                if (self.options.scrollHistory) {

                  if (window.location.hash !== "#" + anchorText) {

                    window.location.replace("#" + anchorText);

                  }
                }

                // If the `showAndHideOnScroll` option is true
                if (self.options.showAndHideOnScroll && self.options.showAndHide) {

                  self._triggerShow(elem, true);

                }

              }, 0);

            });

          });
        }

      },

      // Show
      // ----
      //      Opens the current sub-header
      show: function(elem, scroll) {

        // Stores the plugin context in the `self` variable
        var self = this,
          element = elem;

        // If the sub-header is not already visible
        if (!elem.is(":visible")) {

          // If the current element does not have any nested subheaders, is not a header, and its parent is not visible
          if (!elem.find(subheaderClass).length && !elem.parent().is(headerClass) && !elem.parent().is(":visible")) {

            // Sets the current element to all of the subheaders within the current header
            elem = elem.parents(subheaderClass).add(elem);

          }

          // If the current element does not have any nested subheaders and is not a header
          else if (!elem.children(subheaderClass).length && !elem.parent().is(headerClass)) {

            // Sets the current element to the closest subheader
            elem = elem.closest(subheaderClass);

          }

          //Determines what jQuery effect to use
          switch (self.options.showEffect) {

            //Uses `no effect`
            case "none":

              elem.show();

              break;

              //Uses the jQuery `show` special effect
            case "show":

              elem.show(self.options.showEffectSpeed);

              break;

              //Uses the jQuery `slideDown` special effect
            case "slideDown":

              elem.slideDown(self.options.showEffectSpeed);

              break;

              //Uses the jQuery `fadeIn` special effect
            case "fadeIn":

              elem.fadeIn(self.options.showEffectSpeed);

              break;

              //If none of the above options were passed, then a `jQueryUI show effect` is expected
            default:

              elem.show();

              break;

          }

        }

        // If the current subheader parent element is a header
        if (elem.parent().is(headerClass)) {

          // Hides all non-active sub-headers
          self.hide($(subheaderClass).not(elem));

        }

        // If the current subheader parent element is not a header
        else {

          // Hides all non-active sub-headers
          self.hide($(subheaderClass).not(elem.closest(headerClass).find(subheaderClass).not(elem.siblings())));

        }

        // Maintains chainablity
        return self;

      },

      // Hide
      // ----
      //      Closes the current sub-header
      hide: function(elem) {

        // Stores the plugin context in the `self` variable
        var self = this;

        //Determines what jQuery effect to use
        switch (self.options.hideEffect) {

          // Uses `no effect`
          case "none":

            elem.hide();

            break;

            // Uses the jQuery `hide` special effect
          case "hide":

            elem.hide(self.options.hideEffectSpeed);

            break;

            // Uses the jQuery `slideUp` special effect
          case "slideUp":

            elem.slideUp(self.options.hideEffectSpeed);

            break;

            // Uses the jQuery `fadeOut` special effect
          case "fadeOut":

            elem.fadeOut(self.options.hideEffectSpeed);

            break;

            // If none of the above options were passed, then a `jqueryUI hide effect` is expected
          default:

            elem.hide();

            break;

        }

        // Maintains chainablity
        return self;
      },

      // _triggerShow
      // ------------
      //      Determines what elements get shown on scroll and click
      _triggerShow: function(elem, scroll) {

        var self = this;

        // If the current element's parent is a header element or the next element is a nested subheader element
        if (elem.parent().is(headerClass) || elem.next().is(subheaderClass)) {

          // Shows the next sub-header element
          self.show(elem.next(subheaderClass), scroll);

        }

        // If the current element's parent is a subheader element
        else if (elem.parent().is(subheaderClass)) {

          // Shows the parent sub-header element
          self.show(elem.parent(), scroll);

        }

        // Maintains chainability
        return self;

      },

      // _addCSSClasses
      // --------------
      //      Adds CSS classes to the newly generated table of contents HTML
      _addCSSClasses: function() {

        // If the user wants a jqueryUI theme
        if (this.options.theme === "jqueryui") {

          this.focusClass = "ui-state-default";

          this.hoverClass = "ui-state-hover";

          //Adds the default styling to the dropdown list
          this.element.addClass("ui-widget").find(".toc-title").addClass("ui-widget-header").end().find("li").addClass("ui-widget-content");

        }

        // If the user wants a twitterBootstrap theme
        else if (this.options.theme === "bootstrap") {

          this.element.find(headerClass + "," + subheaderClass).addClass("nav nav-list");

          this.focusClass = "active";

        }

        // If the user wants a twitterBootstrap theme
        else if (this.options.theme === "bootstrap3") {

          this.element.find(headerClass + "," + subheaderClass).addClass("list-group");

          this.element.find(itemClass).addClass("list-group-item");

          this.focusClass = "active";

        }

        // If a user does not want a prebuilt theme
        else {

          // Adds more neutral classes (instead of jqueryui)

          this.focusClass = tocFocusClassName;

          this.hoverClass = tocHoverClassName;

        }

        //Maintains chainability
        return this;

      },

      // setOption
      // ---------
      //      Sets a single Tocify option after the plugin is invoked
      setOption: function() {

        // Calls the jQueryUI Widget Factory setOption method
        $.Widget.prototype._setOption.apply(this, arguments);

      },

      // setOptions
      // ----------
      //      Sets a single or multiple Tocify options after the plugin is invoked
      setOptions: function() {

        // Calls the jQueryUI Widget Factory setOptions method
        $.Widget.prototype._setOptions.apply(this, arguments);

      },

      // _scrollTo
      // ---------
      //      Scrolls to a specific element
      _scrollTo: function(elem) {

        var self = this,
          duration = self.options.smoothScroll || 0,
          scrollTo = self.options.scrollTo,
          currentDiv = $('div[data-unique="' + elem.attr("data-unique") + '"]');

        if (!currentDiv.length) {

          return self;

        }

        // Once all animations on the page are complete, this callback function will be called
        $("html, body").promise().done(function() {

          // Animates the html and body element scrolltops
          $("html, body").animate({

            // Sets the jQuery `scrollTop` to the top offset of the HTML div tag that matches the current list item's `data-unique` tag
            "scrollTop": currentDiv.offset().top - ($.isFunction(scrollTo) ? scrollTo.call() : scrollTo) + "px"

          }, {

            // Sets the smoothScroll animation time duration to the smoothScrollSpeed option
            "duration": duration

          });

        });

        // Maintains chainability
        return self;

      }

    });

  })); //end of plugin
</script>
<script>

/**
 * jQuery Plugin: Sticky Tabs
 *
 * @author Aidan Lister <aidan@php.net>
 * adapted by Ruben Arslan to activate parent tabs too
 * http://www.aidanlister.com/2014/03/persisting-the-tab-state-in-bootstrap/
 */
(function($) {
  "use strict";
  $.fn.rmarkdownStickyTabs = function() {
    var context = this;
    // Show the tab corresponding with the hash in the URL, or the first tab
    var showStuffFromHash = function() {
      var hash = window.location.hash;
      var selector = hash ? 'a[href="' + hash + '"]' : 'li.active > a';
      var $selector = $(selector, context);
      if($selector.data('toggle') === "tab") {
        $selector.tab('show');
        // walk up the ancestors of this element, show any hidden tabs
        $selector.parents('.section.tabset').each(function(i, elm) {
          var link = $('a[href="#' + $(elm).attr('id') + '"]');
          if(link.data('toggle') === "tab") {
            link.tab("show");
          }
        });
      }
    };


    // Set the correct tab when the page loads
    showStuffFromHash(context);

    // Set the correct tab when a user uses their back/forward button
    $(window).on('hashchange', function() {
      showStuffFromHash(context);
    });

    // Change the URL when tabs are clicked
    $('a', context).on('click', function(e) {
      history.pushState(null, null, this.href);
      showStuffFromHash(context);
    });

    return this;
  };
}(jQuery));

window.buildTabsets = function(tocID) {

  // build a tabset from a section div with the .tabset class
  function buildTabset(tabset) {

    // check for fade and pills options
    var fade = tabset.hasClass("tabset-fade");
    var pills = tabset.hasClass("tabset-pills");
    var navClass = pills ? "nav-pills" : "nav-tabs";

    // determine the heading level of the tabset and tabs
    var match = tabset.attr('class').match(/level(\d) /);
    if (match === null)
      return;
    var tabsetLevel = Number(match[1]);
    var tabLevel = tabsetLevel + 1;

    // find all subheadings immediately below
    var tabs = tabset.find("div.section.level" + tabLevel);
    if (!tabs.length)
      return;

    // create tablist and tab-content elements
    var tabList = $('<ul class="nav ' + navClass + '" role="tablist"></ul>');
    $(tabs[0]).before(tabList);
    var tabContent = $('<div class="tab-content"></div>');
    $(tabs[0]).before(tabContent);

    // build the tabset
    var activeTab = 0;
    tabs.each(function(i) {

      // get the tab div
      var tab = $(tabs[i]);

      // get the id then sanitize it for use with bootstrap tabs
      var id = tab.attr('id');

      // see if this is marked as the active tab
      if (tab.hasClass('active'))
        activeTab = i;

      // remove any table of contents entries associated with
      // this ID (since we'll be removing the heading element)
      $("div#" + tocID + " li a[href='#" + id + "']").parent().remove();

      // sanitize the id for use with bootstrap tabs
      id = id.replace(/[.\/?&!#<>]/g, '').replace(/\s/g, '_');
      tab.attr('id', id);

      // get the heading element within it, grab it's text, then remove it
      var heading = tab.find('h' + tabLevel + ':first');
      var headingText = heading.html();
      heading.remove();

      // build and append the tab list item
      var a = $('<a role="tab" data-toggle="tab">' + headingText + '</a>');
      a.attr('href', '#' + id);
      a.attr('aria-controls', id);
      var li = $('<li role="presentation"></li>');
      li.append(a);
      tabList.append(li);

      // set it's attributes
      tab.attr('role', 'tabpanel');
      tab.addClass('tab-pane');
      tab.addClass('tabbed-pane');
      if (fade)
        tab.addClass('fade');

      // move it into the tab content div
      tab.detach().appendTo(tabContent);
    });

    // set active tab
    $(tabList.children('li')[activeTab]).addClass('active');
    var active = $(tabContent.children('div.section')[activeTab]);
    active.addClass('active');
    if (fade)
      active.addClass('in');

    if (tabset.hasClass("tabset-sticky"))
      tabset.rmarkdownStickyTabs();
  }

  // convert section divs with the .tabset class to tabsets
  var tabsets = $("div.section.tabset");
  tabsets.each(function(i) {
    buildTabset($(tabsets[i]));
  });
};

</script>
<style type="text/css">.hljs-literal {
color: #990073;
}
.hljs-number {
color: #099;
}
.hljs-comment {
color: #998;
font-style: italic;
}
.hljs-keyword {
color: #900;
font-weight: bold;
}
.hljs-string {
color: #d14;
}
</style>
<script src="data:application/javascript;base64,/*! highlight.js v9.12.0 | BSD3 License | git.io/hljslicense */
!function(e){var n="object"==typeof window&&window||"object"==typeof self&&self;"undefined"!=typeof exports?e(exports):n&&(n.hljs=e({}),"function"==typeof define&&define.amd&&define([],function(){return n.hljs}))}(function(e){function n(e){return e.replace(/&/g,"&amp;").replace(/</g,"&lt;").replace(/>/g,"&gt;")}function t(e){return e.nodeName.toLowerCase()}function r(e,n){var t=e&&e.exec(n);return t&&0===t.index}function a(e){return k.test(e)}function i(e){var n,t,r,i,o=e.className+" ";if(o+=e.parentNode?e.parentNode.className:"",t=B.exec(o))return w(t[1])?t[1]:"no-highlight";for(o=o.split(/\s+/),n=0,r=o.length;r>n;n++)if(i=o[n],a(i)||w(i))return i}function o(e){var n,t={},r=Array.prototype.slice.call(arguments,1);for(n in e)t[n]=e[n];return r.forEach(function(e){for(n in e)t[n]=e[n]}),t}function u(e){var n=[];return function r(e,a){for(var i=e.firstChild;i;i=i.nextSibling)3===i.nodeType?a+=i.nodeValue.length:1===i.nodeType&&(n.push({event:"start",offset:a,node:i}),a=r(i,a),t(i).match(/br|hr|img|input/)||n.push({event:"stop",offset:a,node:i}));return a}(e,0),n}function c(e,r,a){function i(){return e.length&&r.length?e[0].offset!==r[0].offset?e[0].offset<r[0].offset?e:r:"start"===r[0].event?e:r:e.length?e:r}function o(e){function r(e){return" "+e.nodeName+'="'+n(e.value).replace('"',"&quot;")+'"'}s+="<"+t(e)+E.map.call(e.attributes,r).join("")+">"}function u(e){s+="</"+t(e)+">"}function c(e){("start"===e.event?o:u)(e.node)}for(var l=0,s="",f=[];e.length||r.length;){var g=i();if(s+=n(a.substring(l,g[0].offset)),l=g[0].offset,g===e){f.reverse().forEach(u);do c(g.splice(0,1)[0]),g=i();while(g===e&&g.length&&g[0].offset===l);f.reverse().forEach(o)}else"start"===g[0].event?f.push(g[0].node):f.pop(),c(g.splice(0,1)[0])}return s+n(a.substr(l))}function l(e){return e.v&&!e.cached_variants&&(e.cached_variants=e.v.map(function(n){return o(e,{v:null},n)})),e.cached_variants||e.eW&&[o(e)]||[e]}function s(e){function n(e){return e&&e.source||e}function t(t,r){return new RegExp(n(t),"m"+(e.cI?"i":"")+(r?"g":""))}function r(a,i){if(!a.compiled){if(a.compiled=!0,a.k=a.k||a.bK,a.k){var o={},u=function(n,t){e.cI&&(t=t.toLowerCase()),t.split(" ").forEach(function(e){var t=e.split("|");o[t[0]]=[n,t[1]?Number(t[1]):1]})};"string"==typeof a.k?u("keyword",a.k):x(a.k).forEach(function(e){u(e,a.k[e])}),a.k=o}a.lR=t(a.l||/\w+/,!0),i&&(a.bK&&(a.b="\\b("+a.bK.split(" ").join("|")+")\\b"),a.b||(a.b=/\B|\b/),a.bR=t(a.b),a.e||a.eW||(a.e=/\B|\b/),a.e&&(a.eR=t(a.e)),a.tE=n(a.e)||"",a.eW&&i.tE&&(a.tE+=(a.e?"|":"")+i.tE)),a.i&&(a.iR=t(a.i)),null==a.r&&(a.r=1),a.c||(a.c=[]),a.c=Array.prototype.concat.apply([],a.c.map(function(e){return l("self"===e?a:e)})),a.c.forEach(function(e){r(e,a)}),a.starts&&r(a.starts,i);var c=a.c.map(function(e){return e.bK?"\\.?("+e.b+")\\.?":e.b}).concat([a.tE,a.i]).map(n).filter(Boolean);a.t=c.length?t(c.join("|"),!0):{exec:function(){return null}}}}r(e)}function f(e,t,a,i){function o(e,n){var t,a;for(t=0,a=n.c.length;a>t;t++)if(r(n.c[t].bR,e))return n.c[t]}function u(e,n){if(r(e.eR,n)){for(;e.endsParent&&e.parent;)e=e.parent;return e}return e.eW?u(e.parent,n):void 0}function c(e,n){return!a&&r(n.iR,e)}function l(e,n){var t=N.cI?n[0].toLowerCase():n[0];return e.k.hasOwnProperty(t)&&e.k[t]}function p(e,n,t,r){var a=r?"":I.classPrefix,i='<span class="'+a,o=t?"":C;return i+=e+'">',i+n+o}function h(){var e,t,r,a;if(!E.k)return n(k);for(a="",t=0,E.lR.lastIndex=0,r=E.lR.exec(k);r;)a+=n(k.substring(t,r.index)),e=l(E,r),e?(B+=e[1],a+=p(e[0],n(r[0]))):a+=n(r[0]),t=E.lR.lastIndex,r=E.lR.exec(k);return a+n(k.substr(t))}function d(){var e="string"==typeof E.sL;if(e&&!y[E.sL])return n(k);var t=e?f(E.sL,k,!0,x[E.sL]):g(k,E.sL.length?E.sL:void 0);return E.r>0&&(B+=t.r),e&&(x[E.sL]=t.top),p(t.language,t.value,!1,!0)}function b(){L+=null!=E.sL?d():h(),k=""}function v(e){L+=e.cN?p(e.cN,"",!0):"",E=Object.create(e,{parent:{value:E}})}function m(e,n){if(k+=e,null==n)return b(),0;var t=o(n,E);if(t)return t.skip?k+=n:(t.eB&&(k+=n),b(),t.rB||t.eB||(k=n)),v(t,n),t.rB?0:n.length;var r=u(E,n);if(r){var a=E;a.skip?k+=n:(a.rE||a.eE||(k+=n),b(),a.eE&&(k=n));do E.cN&&(L+=C),E.skip||(B+=E.r),E=E.parent;while(E!==r.parent);return r.starts&&v(r.starts,""),a.rE?0:n.length}if(c(n,E))throw new Error('Illegal lexeme "'+n+'" for mode "'+(E.cN||"<unnamed>")+'"');return k+=n,n.length||1}var N=w(e);if(!N)throw new Error('Unknown language: "'+e+'"');s(N);var R,E=i||N,x={},L="";for(R=E;R!==N;R=R.parent)R.cN&&(L=p(R.cN,"",!0)+L);var k="",B=0;try{for(var M,j,O=0;;){if(E.t.lastIndex=O,M=E.t.exec(t),!M)break;j=m(t.substring(O,M.index),M[0]),O=M.index+j}for(m(t.substr(O)),R=E;R.parent;R=R.parent)R.cN&&(L+=C);return{r:B,value:L,language:e,top:E}}catch(T){if(T.message&&-1!==T.message.indexOf("Illegal"))return{r:0,value:n(t)};throw T}}function g(e,t){t=t||I.languages||x(y);var r={r:0,value:n(e)},a=r;return t.filter(w).forEach(function(n){var t=f(n,e,!1);t.language=n,t.r>a.r&&(a=t),t.r>r.r&&(a=r,r=t)}),a.language&&(r.second_best=a),r}function p(e){return I.tabReplace||I.useBR?e.replace(M,function(e,n){return I.useBR&&"\n"===e?"<br>":I.tabReplace?n.replace(/\t/g,I.tabReplace):""}):e}function h(e,n,t){var r=n?L[n]:t,a=[e.trim()];return e.match(/\bhljs\b/)||a.push("hljs"),-1===e.indexOf(r)&&a.push(r),a.join(" ").trim()}function d(e){var n,t,r,o,l,s=i(e);a(s)||(I.useBR?(n=document.createElementNS("http://www.w3.org/1999/xhtml","div"),n.innerHTML=e.innerHTML.replace(/\n/g,"").replace(/<br[ \/]*>/g,"\n")):n=e,l=n.textContent,r=s?f(s,l,!0):g(l),t=u(n),t.length&&(o=document.createElementNS("http://www.w3.org/1999/xhtml","div"),o.innerHTML=r.value,r.value=c(t,u(o),l)),r.value=p(r.value),e.innerHTML=r.value,e.className=h(e.className,s,r.language),e.result={language:r.language,re:r.r},r.second_best&&(e.second_best={language:r.second_best.language,re:r.second_best.r}))}function b(e){I=o(I,e)}function v(){if(!v.called){v.called=!0;var e=document.querySelectorAll("pre code");E.forEach.call(e,d)}}function m(){addEventListener("DOMContentLoaded",v,!1),addEventListener("load",v,!1)}function N(n,t){var r=y[n]=t(e);r.aliases&&r.aliases.forEach(function(e){L[e]=n})}function R(){return x(y)}function w(e){return e=(e||"").toLowerCase(),y[e]||y[L[e]]}var E=[],x=Object.keys,y={},L={},k=/^(no-?highlight|plain|text)$/i,B=/\blang(?:uage)?-([\w-]+)\b/i,M=/((^(<[^>]+>|\t|)+|(?:\n)))/gm,C="</span>",I={classPrefix:"hljs-",tabReplace:null,useBR:!1,languages:void 0};return e.highlight=f,e.highlightAuto=g,e.fixMarkup=p,e.highlightBlock=d,e.configure=b,e.initHighlighting=v,e.initHighlightingOnLoad=m,e.registerLanguage=N,e.listLanguages=R,e.getLanguage=w,e.inherit=o,e.IR="[a-zA-Z]\\w*",e.UIR="[a-zA-Z_]\\w*",e.NR="\\b\\d+(\\.\\d+)?",e.CNR="(-?)(\\b0[xX][a-fA-F0-9]+|(\\b\\d+(\\.\\d*)?|\\.\\d+)([eE][-+]?\\d+)?)",e.BNR="\\b(0b[01]+)",e.RSR="!|!=|!==|%|%=|&|&&|&=|\\*|\\*=|\\+|\\+=|,|-|-=|/=|/|:|;|<<|<<=|<=|<|===|==|=|>>>=|>>=|>=|>>>|>>|>|\\?|\\[|\\{|\\(|\\^|\\^=|\\||\\|=|\\|\\||~",e.BE={b:"\\\\[\\s\\S]",r:0},e.ASM={cN:"string",b:"'",e:"'",i:"\\n",c:[e.BE]},e.QSM={cN:"string",b:'"',e:'"',i:"\\n",c:[e.BE]},e.PWM={b:/\b(a|an|the|are|I'm|isn't|don't|doesn't|won't|but|just|should|pretty|simply|enough|gonna|going|wtf|so|such|will|you|your|they|like|more)\b/},e.C=function(n,t,r){var a=e.inherit({cN:"comment",b:n,e:t,c:[]},r||{});return a.c.push(e.PWM),a.c.push({cN:"doctag",b:"(?:TODO|FIXME|NOTE|BUG|XXX):",r:0}),a},e.CLCM=e.C("//","$"),e.CBCM=e.C("/\\*","\\*/"),e.HCM=e.C("#","$"),e.NM={cN:"number",b:e.NR,r:0},e.CNM={cN:"number",b:e.CNR,r:0},e.BNM={cN:"number",b:e.BNR,r:0},e.CSSNM={cN:"number",b:e.NR+"(%|em|ex|ch|rem|vw|vh|vmin|vmax|cm|mm|in|pt|pc|px|deg|grad|rad|turn|s|ms|Hz|kHz|dpi|dpcm|dppx)?",r:0},e.RM={cN:"regexp",b:/\//,e:/\/[gimuy]*/,i:/\n/,c:[e.BE,{b:/\[/,e:/\]/,r:0,c:[e.BE]}]},e.TM={cN:"title",b:e.IR,r:0},e.UTM={cN:"title",b:e.UIR,r:0},e.METHOD_GUARD={b:"\\.\\s*"+e.UIR,r:0},e});hljs.registerLanguage("sql",function(e){var t=e.C("--","$");return{cI:!0,i:/[<>{}*#]/,c:[{bK:"begin end start commit rollback savepoint lock alter create drop rename call delete do handler insert load replace select truncate update set show pragma grant merge describe use explain help declare prepare execute deallocate release unlock purge reset change stop analyze cache flush optimize repair kill install uninstall checksum restore check backup revoke comment",e:/;/,eW:!0,l:/[\w\.]+/,k:{keyword:"abort abs absolute acc acce accep accept access accessed accessible account acos action activate add addtime admin administer advanced advise aes_decrypt aes_encrypt after agent aggregate ali alia alias allocate allow alter always analyze ancillary and any anydata anydataset anyschema anytype apply archive archived archivelog are as asc ascii asin assembly assertion associate asynchronous at atan atn2 attr attri attrib attribu attribut attribute attributes audit authenticated authentication authid authors auto autoallocate autodblink autoextend automatic availability avg backup badfile basicfile before begin beginning benchmark between bfile bfile_base big bigfile bin binary_double binary_float binlog bit_and bit_count bit_length bit_or bit_xor bitmap blob_base block blocksize body both bound buffer_cache buffer_pool build bulk by byte byteordermark bytes cache caching call calling cancel capacity cascade cascaded case cast catalog category ceil ceiling chain change changed char_base char_length character_length characters characterset charindex charset charsetform charsetid check checksum checksum_agg child choose chr chunk class cleanup clear client clob clob_base clone close cluster_id cluster_probability cluster_set clustering coalesce coercibility col collate collation collect colu colum column column_value columns columns_updated comment commit compact compatibility compiled complete composite_limit compound compress compute concat concat_ws concurrent confirm conn connec connect connect_by_iscycle connect_by_isleaf connect_by_root connect_time connection consider consistent constant constraint constraints constructor container content contents context contributors controlfile conv convert convert_tz corr corr_k corr_s corresponding corruption cos cost count count_big counted covar_pop covar_samp cpu_per_call cpu_per_session crc32 create creation critical cross cube cume_dist curdate current current_date current_time current_timestamp current_user cursor curtime customdatum cycle data database databases datafile datafiles datalength date_add date_cache date_format date_sub dateadd datediff datefromparts datename datepart datetime2fromparts day day_to_second dayname dayofmonth dayofweek dayofyear days db_role_change dbtimezone ddl deallocate declare decode decompose decrement decrypt deduplicate def defa defau defaul default defaults deferred defi defin define degrees delayed delegate delete delete_all delimited demand dense_rank depth dequeue des_decrypt des_encrypt des_key_file desc descr descri describ describe descriptor deterministic diagnostics difference dimension direct_load directory disable disable_all disallow disassociate discardfile disconnect diskgroup distinct distinctrow distribute distributed div do document domain dotnet double downgrade drop dumpfile duplicate duration each edition editionable editions element ellipsis else elsif elt empty enable enable_all enclosed encode encoding encrypt end end-exec endian enforced engine engines enqueue enterprise entityescaping eomonth error errors escaped evalname evaluate event eventdata events except exception exceptions exchange exclude excluding execu execut execute exempt exists exit exp expire explain export export_set extended extent external external_1 external_2 externally extract failed failed_login_attempts failover failure far fast feature_set feature_value fetch field fields file file_name_convert filesystem_like_logging final finish first first_value fixed flash_cache flashback floor flush following follows for forall force form forma format found found_rows freelist freelists freepools fresh from from_base64 from_days ftp full function general generated get get_format get_lock getdate getutcdate global global_name globally go goto grant grants greatest group group_concat group_id grouping grouping_id groups gtid_subtract guarantee guard handler hash hashkeys having hea head headi headin heading heap help hex hierarchy high high_priority hosts hour http id ident_current ident_incr ident_seed identified identity idle_time if ifnull ignore iif ilike ilm immediate import in include including increment index indexes indexing indextype indicator indices inet6_aton inet6_ntoa inet_aton inet_ntoa infile initial initialized initially initrans inmemory inner innodb input insert install instance instantiable instr interface interleaved intersect into invalidate invisible is is_free_lock is_ipv4 is_ipv4_compat is_not is_not_null is_used_lock isdate isnull isolation iterate java join json json_exists keep keep_duplicates key keys kill language large last last_day last_insert_id last_value lax lcase lead leading least leaves left len lenght length less level levels library like like2 like4 likec limit lines link list listagg little ln load load_file lob lobs local localtime localtimestamp locate locator lock locked log log10 log2 logfile logfiles logging logical logical_reads_per_call logoff logon logs long loop low low_priority lower lpad lrtrim ltrim main make_set makedate maketime managed management manual map mapping mask master master_pos_wait match matched materialized max maxextents maximize maxinstances maxlen maxlogfiles maxloghistory maxlogmembers maxsize maxtrans md5 measures median medium member memcompress memory merge microsecond mid migration min minextents minimum mining minus minute minvalue missing mod mode model modification modify module monitoring month months mount move movement multiset mutex name name_const names nan national native natural nav nchar nclob nested never new newline next nextval no no_write_to_binlog noarchivelog noaudit nobadfile nocheck nocompress nocopy nocycle nodelay nodiscardfile noentityescaping noguarantee nokeep nologfile nomapping nomaxvalue nominimize nominvalue nomonitoring none noneditionable nonschema noorder nopr nopro noprom nopromp noprompt norely noresetlogs noreverse normal norowdependencies noschemacheck noswitch not nothing notice notrim novalidate now nowait nth_value nullif nulls num numb numbe nvarchar nvarchar2 object ocicoll ocidate ocidatetime ociduration ociinterval ociloblocator ocinumber ociref ocirefcursor ocirowid ocistring ocitype oct octet_length of off offline offset oid oidindex old on online only opaque open operations operator optimal optimize option optionally or oracle oracle_date oradata ord ordaudio orddicom orddoc order ordimage ordinality ordvideo organization orlany orlvary out outer outfile outline output over overflow overriding package pad parallel parallel_enable parameters parent parse partial partition partitions pascal passing password password_grace_time password_lock_time password_reuse_max password_reuse_time password_verify_function patch path patindex pctincrease pctthreshold pctused pctversion percent percent_rank percentile_cont percentile_disc performance period period_add period_diff permanent physical pi pipe pipelined pivot pluggable plugin policy position post_transaction pow power pragma prebuilt precedes preceding precision prediction prediction_cost prediction_details prediction_probability prediction_set prepare present preserve prior priority private private_sga privileges procedural procedure procedure_analyze processlist profiles project prompt protection public publishingservername purge quarter query quick quiesce quota quotename radians raise rand range rank raw read reads readsize rebuild record records recover recovery recursive recycle redo reduced ref reference referenced references referencing refresh regexp_like register regr_avgx regr_avgy regr_count regr_intercept regr_r2 regr_slope regr_sxx regr_sxy reject rekey relational relative relaylog release release_lock relies_on relocate rely rem remainder rename repair repeat replace replicate replication required reset resetlogs resize resource respect restore restricted result result_cache resumable resume retention return returning returns reuse reverse revoke right rlike role roles rollback rolling rollup round row row_count rowdependencies rowid rownum rows rtrim rules safe salt sample save savepoint sb1 sb2 sb4 scan schema schemacheck scn scope scroll sdo_georaster sdo_topo_geometry search sec_to_time second section securefile security seed segment select self sequence sequential serializable server servererror session session_user sessions_per_user set sets settings sha sha1 sha2 share shared shared_pool short show shrink shutdown si_averagecolor si_colorhistogram si_featurelist si_positionalcolor si_stillimage si_texture siblings sid sign sin size size_t sizes skip slave sleep smalldatetimefromparts smallfile snapshot some soname sort soundex source space sparse spfile split sql sql_big_result sql_buffer_result sql_cache sql_calc_found_rows sql_small_result sql_variant_property sqlcode sqldata sqlerror sqlname sqlstate sqrt square standalone standby start starting startup statement static statistics stats_binomial_test stats_crosstab stats_ks_test stats_mode stats_mw_test stats_one_way_anova stats_t_test_ stats_t_test_indep stats_t_test_one stats_t_test_paired stats_wsr_test status std stddev stddev_pop stddev_samp stdev stop storage store stored str str_to_date straight_join strcmp strict string struct stuff style subdate subpartition subpartitions substitutable substr substring subtime subtring_index subtype success sum suspend switch switchoffset switchover sync synchronous synonym sys sys_xmlagg sysasm sysaux sysdate sysdatetimeoffset sysdba sysoper system system_user sysutcdatetime table tables tablespace tan tdo template temporary terminated tertiary_weights test than then thread through tier ties time time_format time_zone timediff timefromparts timeout timestamp timestampadd timestampdiff timezone_abbr timezone_minute timezone_region to to_base64 to_date to_days to_seconds todatetimeoffset trace tracking transaction transactional translate translation treat trigger trigger_nestlevel triggers trim truncate try_cast try_convert try_parse type ub1 ub2 ub4 ucase unarchived unbounded uncompress under undo unhex unicode uniform uninstall union unique unix_timestamp unknown unlimited unlock unpivot unrecoverable unsafe unsigned until untrusted unusable unused update updated upgrade upped upper upsert url urowid usable usage use use_stored_outlines user user_data user_resources users using utc_date utc_timestamp uuid uuid_short validate validate_password_strength validation valist value values var var_samp varcharc vari varia variab variabl variable variables variance varp varraw varrawc varray verify version versions view virtual visible void wait wallet warning warnings week weekday weekofyear wellformed when whene whenev wheneve whenever where while whitespace with within without work wrapped xdb xml xmlagg xmlattributes xmlcast xmlcolattval xmlelement xmlexists xmlforest xmlindex xmlnamespaces xmlpi xmlquery xmlroot xmlschema xmlserialize xmltable xmltype xor year year_to_month years yearweek",literal:"true false null",built_in:"array bigint binary bit blob boolean char character date dec decimal float int int8 integer interval number numeric real record serial serial8 smallint text varchar varying void"},c:[{cN:"string",b:"'",e:"'",c:[e.BE,{b:"''"}]},{cN:"string",b:'"',e:'"',c:[e.BE,{b:'""'}]},{cN:"string",b:"`",e:"`",c:[e.BE]},e.CNM,e.CBCM,t]},e.CBCM,t]}});hljs.registerLanguage("r",function(e){var r="([a-zA-Z]|\\.[a-zA-Z.])[a-zA-Z0-9._]*";return{c:[e.HCM,{b:r,l:r,k:{keyword:"function if in break next repeat else for return switch while try tryCatch stop warning require library attach detach source setMethod setGeneric setGroupGeneric setClass ...",literal:"NULL NA TRUE FALSE T F Inf NaN NA_integer_|10 NA_real_|10 NA_character_|10 NA_complex_|10"},r:0},{cN:"number",b:"0[xX][0-9a-fA-F]+[Li]?\\b",r:0},{cN:"number",b:"\\d+(?:[eE][+\\-]?\\d*)?L\\b",r:0},{cN:"number",b:"\\d+\\.(?!\\d)(?:i\\b)?",r:0},{cN:"number",b:"\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",r:0},{cN:"number",b:"\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",r:0},{b:"`",e:"`",r:0},{cN:"string",c:[e.BE],v:[{b:'"',e:'"'},{b:"'",e:"'"}]}]}});hljs.registerLanguage("perl",function(e){var t="getpwent getservent quotemeta msgrcv scalar kill dbmclose undef lc ma syswrite tr send umask sysopen shmwrite vec qx utime local oct semctl localtime readpipe do return format read sprintf dbmopen pop getpgrp not getpwnam rewinddir qqfileno qw endprotoent wait sethostent bless s|0 opendir continue each sleep endgrent shutdown dump chomp connect getsockname die socketpair close flock exists index shmgetsub for endpwent redo lstat msgctl setpgrp abs exit select print ref gethostbyaddr unshift fcntl syscall goto getnetbyaddr join gmtime symlink semget splice x|0 getpeername recv log setsockopt cos last reverse gethostbyname getgrnam study formline endhostent times chop length gethostent getnetent pack getprotoent getservbyname rand mkdir pos chmod y|0 substr endnetent printf next open msgsnd readdir use unlink getsockopt getpriority rindex wantarray hex system getservbyport endservent int chr untie rmdir prototype tell listen fork shmread ucfirst setprotoent else sysseek link getgrgid shmctl waitpid unpack getnetbyname reset chdir grep split require caller lcfirst until warn while values shift telldir getpwuid my getprotobynumber delete and sort uc defined srand accept package seekdir getprotobyname semop our rename seek if q|0 chroot sysread setpwent no crypt getc chown sqrt write setnetent setpriority foreach tie sin msgget map stat getlogin unless elsif truncate exec keys glob tied closedirioctl socket readlink eval xor readline binmode setservent eof ord bind alarm pipe atan2 getgrent exp time push setgrent gt lt or ne m|0 break given say state when",r={cN:"subst",b:"[$@]\\{",e:"\\}",k:t},s={b:"->{",e:"}"},n={v:[{b:/\$\d/},{b:/[\$%@](\^\w\b|#\w+(::\w+)*|{\w+}|\w+(::\w*)*)/},{b:/[\$%@][^\s\w{]/,r:0}]},i=[e.BE,r,n],o=[n,e.HCM,e.C("^\\=\\w","\\=cut",{eW:!0}),s,{cN:"string",c:i,v:[{b:"q[qwxr]?\\s*\\(",e:"\\)",r:5},{b:"q[qwxr]?\\s*\\[",e:"\\]",r:5},{b:"q[qwxr]?\\s*\\{",e:"\\}",r:5},{b:"q[qwxr]?\\s*\\|",e:"\\|",r:5},{b:"q[qwxr]?\\s*\\<",e:"\\>",r:5},{b:"qw\\s+q",e:"q",r:5},{b:"'",e:"'",c:[e.BE]},{b:'"',e:'"'},{b:"`",e:"`",c:[e.BE]},{b:"{\\w+}",c:[],r:0},{b:"-?\\w+\\s*\\=\\>",c:[],r:0}]},{cN:"number",b:"(\\b0[0-7_]+)|(\\b0x[0-9a-fA-F_]+)|(\\b[1-9][0-9_]*(\\.[0-9_]+)?)|[0_]\\b",r:0},{b:"(\\/\\/|"+e.RSR+"|\\b(split|return|print|reverse|grep)\\b)\\s*",k:"split return print reverse grep",r:0,c:[e.HCM,{cN:"regexp",b:"(s|tr|y)/(\\\\.|[^/])*/(\\\\.|[^/])*/[a-z]*",r:10},{cN:"regexp",b:"(m|qr)?/",e:"/[a-z]*",c:[e.BE],r:0}]},{cN:"function",bK:"sub",e:"(\\s*\\(.*?\\))?[;{]",eE:!0,r:5,c:[e.TM]},{b:"-\\w\\b",r:0},{b:"^__DATA__$",e:"^__END__$",sL:"mojolicious",c:[{b:"^@@.*",e:"$",cN:"comment"}]}];return r.c=o,s.c=o,{aliases:["pl","pm"],l:/[\w\.]+/,k:t,c:o}});hljs.registerLanguage("ini",function(e){var b={cN:"string",c:[e.BE],v:[{b:"'''",e:"'''",r:10},{b:'"""',e:'"""',r:10},{b:'"',e:'"'},{b:"'",e:"'"}]};return{aliases:["toml"],cI:!0,i:/\S/,c:[e.C(";","$"),e.HCM,{cN:"section",b:/^\s*\[+/,e:/\]+/},{b:/^[a-z0-9\[\]_-]+\s*=\s*/,e:"$",rB:!0,c:[{cN:"attr",b:/[a-z0-9\[\]_-]+/},{b:/=/,eW:!0,r:0,c:[{cN:"literal",b:/\bon|off|true|false|yes|no\b/},{cN:"variable",v:[{b:/\$[\w\d"][\w\d_]*/},{b:/\$\{(.*?)}/}]},b,{cN:"number",b:/([\+\-]+)?[\d]+_[\d_]+/},e.NM]}]}]}});hljs.registerLanguage("diff",function(e){return{aliases:["patch"],c:[{cN:"meta",r:10,v:[{b:/^@@ +\-\d+,\d+ +\+\d+,\d+ +@@$/},{b:/^\*\*\* +\d+,\d+ +\*\*\*\*$/},{b:/^\-\-\- +\d+,\d+ +\-\-\-\-$/}]},{cN:"comment",v:[{b:/Index: /,e:/$/},{b:/={3,}/,e:/$/},{b:/^\-{3}/,e:/$/},{b:/^\*{3} /,e:/$/},{b:/^\+{3}/,e:/$/},{b:/\*{5}/,e:/\*{5}$/}]},{cN:"addition",b:"^\\+",e:"$"},{cN:"deletion",b:"^\\-",e:"$"},{cN:"addition",b:"^\\!",e:"$"}]}});hljs.registerLanguage("go",function(e){var t={keyword:"break default func interface select case map struct chan else goto package switch const fallthrough if range type continue for import return var go defer bool byte complex64 complex128 float32 float64 int8 int16 int32 int64 string uint8 uint16 uint32 uint64 int uint uintptr rune",literal:"true false iota nil",built_in:"append cap close complex copy imag len make new panic print println real recover delete"};return{aliases:["golang"],k:t,i:"</",c:[e.CLCM,e.CBCM,{cN:"string",v:[e.QSM,{b:"'",e:"[^\\\\]'"},{b:"`",e:"`"}]},{cN:"number",v:[{b:e.CNR+"[dflsi]",r:1},e.CNM]},{b:/:=/},{cN:"function",bK:"func",e:/\s*\{/,eE:!0,c:[e.TM,{cN:"params",b:/\(/,e:/\)/,k:t,i:/["']/}]}]}});hljs.registerLanguage("bash",function(e){var t={cN:"variable",v:[{b:/\$[\w\d#@][\w\d_]*/},{b:/\$\{(.*?)}/}]},s={cN:"string",b:/"/,e:/"/,c:[e.BE,t,{cN:"variable",b:/\$\(/,e:/\)/,c:[e.BE]}]},a={cN:"string",b:/'/,e:/'/};return{aliases:["sh","zsh"],l:/\b-?[a-z\._]+\b/,k:{keyword:"if then else elif fi for while in do done case esac function",literal:"true false",built_in:"break cd continue eval exec exit export getopts hash pwd readonly return shift test times trap umask unset alias bind builtin caller command declare echo enable help let local logout mapfile printf read readarray source type typeset ulimit unalias set shopt autoload bg bindkey bye cap chdir clone comparguments compcall compctl compdescribe compfiles compgroups compquote comptags comptry compvalues dirs disable disown echotc echoti emulate fc fg float functions getcap getln history integer jobs kill limit log noglob popd print pushd pushln rehash sched setcap setopt stat suspend ttyctl unfunction unhash unlimit unsetopt vared wait whence where which zcompile zformat zftp zle zmodload zparseopts zprof zpty zregexparse zsocket zstyle ztcp",_:"-ne -eq -lt -gt -f -d -e -s -l -a"},c:[{cN:"meta",b:/^#![^\n]+sh\s*$/,r:10},{cN:"function",b:/\w[\w\d_]*\s*\(\s*\)\s*\{/,rB:!0,c:[e.inherit(e.TM,{b:/\w[\w\d_]*/})],r:0},e.HCM,s,a,t]}});hljs.registerLanguage("python",function(e){var r={keyword:"and elif is global as in if from raise for except finally print import pass return exec else break not with class assert yield try while continue del or def lambda async await nonlocal|10 None True False",built_in:"Ellipsis NotImplemented"},b={cN:"meta",b:/^(>>>|\.\.\.) /},c={cN:"subst",b:/\{/,e:/\}/,k:r,i:/#/},a={cN:"string",c:[e.BE],v:[{b:/(u|b)?r?'''/,e:/'''/,c:[b],r:10},{b:/(u|b)?r?"""/,e:/"""/,c:[b],r:10},{b:/(fr|rf|f)'''/,e:/'''/,c:[b,c]},{b:/(fr|rf|f)"""/,e:/"""/,c:[b,c]},{b:/(u|r|ur)'/,e:/'/,r:10},{b:/(u|r|ur)"/,e:/"/,r:10},{b:/(b|br)'/,e:/'/},{b:/(b|br)"/,e:/"/},{b:/(fr|rf|f)'/,e:/'/,c:[c]},{b:/(fr|rf|f)"/,e:/"/,c:[c]},e.ASM,e.QSM]},s={cN:"number",r:0,v:[{b:e.BNR+"[lLjJ]?"},{b:"\\b(0o[0-7]+)[lLjJ]?"},{b:e.CNR+"[lLjJ]?"}]},i={cN:"params",b:/\(/,e:/\)/,c:["self",b,s,a]};return c.c=[a,s,b],{aliases:["py","gyp"],k:r,i:/(<\/|->|\?)|=>/,c:[b,s,a,e.HCM,{v:[{cN:"function",bK:"def"},{cN:"class",bK:"class"}],e:/:/,i:/[${=;\n,]/,c:[e.UTM,i,{b:/->/,eW:!0,k:"None"}]},{cN:"meta",b:/^[\t ]*@/,e:/$/},{b:/\b(print|exec)\(/}]}});hljs.registerLanguage("julia",function(e){var r={keyword:"in isa where baremodule begin break catch ccall const continue do else elseif end export false finally for function global if import importall let local macro module quote return true try using while type immutable abstract bitstype typealias ",literal:"true false ARGS C_NULL DevNull ENDIAN_BOM ENV I Inf Inf16 Inf32 Inf64 InsertionSort JULIA_HOME LOAD_PATH MergeSort NaN NaN16 NaN32 NaN64 PROGRAM_FILE QuickSort RoundDown RoundFromZero RoundNearest RoundNearestTiesAway RoundNearestTiesUp RoundToZero RoundUp STDERR STDIN STDOUT VERSION catalan e|0 eu|0 eulergamma golden im nothing pi γ π φ ",built_in:"ANY AbstractArray AbstractChannel AbstractFloat AbstractMatrix AbstractRNG AbstractSerializer AbstractSet AbstractSparseArray AbstractSparseMatrix AbstractSparseVector AbstractString AbstractUnitRange AbstractVecOrMat AbstractVector Any ArgumentError Array AssertionError Associative Base64DecodePipe Base64EncodePipe Bidiagonal BigFloat BigInt BitArray BitMatrix BitVector Bool BoundsError BufferStream CachingPool CapturedException CartesianIndex CartesianRange Cchar Cdouble Cfloat Channel Char Cint Cintmax_t Clong Clonglong ClusterManager Cmd CodeInfo Colon Complex Complex128 Complex32 Complex64 CompositeException Condition ConjArray ConjMatrix ConjVector Cptrdiff_t Cshort Csize_t Cssize_t Cstring Cuchar Cuint Cuintmax_t Culong Culonglong Cushort Cwchar_t Cwstring DataType Date DateFormat DateTime DenseArray DenseMatrix DenseVecOrMat DenseVector Diagonal Dict DimensionMismatch Dims DirectIndexString Display DivideError DomainError EOFError EachLine Enum Enumerate ErrorException Exception ExponentialBackOff Expr Factorization FileMonitor Float16 Float32 Float64 Function Future GlobalRef GotoNode HTML Hermitian IO IOBuffer IOContext IOStream IPAddr IPv4 IPv6 IndexCartesian IndexLinear IndexStyle InexactError InitError Int Int128 Int16 Int32 Int64 Int8 IntSet Integer InterruptException InvalidStateException Irrational KeyError LabelNode LinSpace LineNumberNode LoadError LowerTriangular MIME Matrix MersenneTwister Method MethodError MethodTable Module NTuple NewvarNode NullException Nullable Number ObjectIdDict OrdinalRange OutOfMemoryError OverflowError Pair ParseError PartialQuickSort PermutedDimsArray Pipe PollingFileWatcher ProcessExitedException Ptr QuoteNode RandomDevice Range RangeIndex Rational RawFD ReadOnlyMemoryError Real ReentrantLock Ref Regex RegexMatch RemoteChannel RemoteException RevString RoundingMode RowVector SSAValue SegmentationFault SerializationState Set SharedArray SharedMatrix SharedVector Signed SimpleVector Slot SlotNumber SparseMatrixCSC SparseVector StackFrame StackOverflowError StackTrace StepRange StepRangeLen StridedArray StridedMatrix StridedVecOrMat StridedVector String SubArray SubString SymTridiagonal Symbol Symmetric SystemError TCPSocket Task Text TextDisplay Timer Tridiagonal Tuple Type TypeError TypeMapEntry TypeMapLevel TypeName TypeVar TypedSlot UDPSocket UInt UInt128 UInt16 UInt32 UInt64 UInt8 UndefRefError UndefVarError UnicodeError UniformScaling Union UnionAll UnitRange Unsigned UpperTriangular Val Vararg VecElement VecOrMat Vector VersionNumber Void WeakKeyDict WeakRef WorkerConfig WorkerPool "},t="[A-Za-z_\\u00A1-\\uFFFF][A-Za-z_0-9\\u00A1-\\uFFFF]*",a={l:t,k:r,i:/<\//},n={cN:"number",b:/(\b0x[\d_]*(\.[\d_]*)?|0x\.\d[\d_]*)p[-+]?\d+|\b0[box][a-fA-F0-9][a-fA-F0-9_]*|(\b\d[\d_]*(\.[\d_]*)?|\.\d[\d_]*)([eEfF][-+]?\d+)?/,r:0},o={cN:"string",b:/'(.|\\[xXuU][a-zA-Z0-9]+)'/},i={cN:"subst",b:/\$\(/,e:/\)/,k:r},l={cN:"variable",b:"\\$"+t},c={cN:"string",c:[e.BE,i,l],v:[{b:/\w*"""/,e:/"""\w*/,r:10},{b:/\w*"/,e:/"\w*/}]},s={cN:"string",c:[e.BE,i,l],b:"`",e:"`"},d={cN:"meta",b:"@"+t},u={cN:"comment",v:[{b:"#=",e:"=#",r:10},{b:"#",e:"$"}]};return a.c=[n,o,c,s,d,u,e.HCM,{cN:"keyword",b:"\\b(((abstract|primitive)\\s+)type|(mutable\\s+)?struct)\\b"},{b:/<:/}],i.c=a.c,a});hljs.registerLanguage("coffeescript",function(e){var c={keyword:"in if for while finally new do return else break catch instanceof throw try this switch continue typeof delete debugger super yield import export from as default await then unless until loop of by when and or is isnt not",literal:"true false null undefined yes no on off",built_in:"npm require console print module global window document"},n="[A-Za-z$_][0-9A-Za-z$_]*",r={cN:"subst",b:/#\{/,e:/}/,k:c},i=[e.BNM,e.inherit(e.CNM,{starts:{e:"(\\s*/)?",r:0}}),{cN:"string",v:[{b:/'''/,e:/'''/,c:[e.BE]},{b:/'/,e:/'/,c:[e.BE]},{b:/"""/,e:/"""/,c:[e.BE,r]},{b:/"/,e:/"/,c:[e.BE,r]}]},{cN:"regexp",v:[{b:"///",e:"///",c:[r,e.HCM]},{b:"//[gim]*",r:0},{b:/\/(?![ *])(\\\/|.)*?\/[gim]*(?=\W|$)/}]},{b:"@"+n},{sL:"javascript",eB:!0,eE:!0,v:[{b:"```",e:"```"},{b:"`",e:"`"}]}];r.c=i;var s=e.inherit(e.TM,{b:n}),t="(\\(.*\\))?\\s*\\B[-=]>",o={cN:"params",b:"\\([^\\(]",rB:!0,c:[{b:/\(/,e:/\)/,k:c,c:["self"].concat(i)}]};return{aliases:["coffee","cson","iced"],k:c,i:/\/\*/,c:i.concat([e.C("###","###"),e.HCM,{cN:"function",b:"^\\s*"+n+"\\s*=\\s*"+t,e:"[-=]>",rB:!0,c:[s,o]},{b:/[:\(,=]\s*/,r:0,c:[{cN:"function",b:t,e:"[-=]>",rB:!0,c:[o]}]},{cN:"class",bK:"class",e:"$",i:/[:="\[\]]/,c:[{bK:"extends",eW:!0,i:/[:="\[\]]/,c:[s]},s]},{b:n+":",e:":",rB:!0,rE:!0,r:0}])}});hljs.registerLanguage("cpp",function(t){var e={cN:"keyword",b:"\\b[a-z\\d_]*_t\\b"},r={cN:"string",v:[{b:'(u8?|U)?L?"',e:'"',i:"\\n",c:[t.BE]},{b:'(u8?|U)?R"',e:'"',c:[t.BE]},{b:"'\\\\?.",e:"'",i:"."}]},s={cN:"number",v:[{b:"\\b(0b[01']+)"},{b:"(-?)\\b([\\d']+(\\.[\\d']*)?|\\.[\\d']+)(u|U|l|L|ul|UL|f|F|b|B)"},{b:"(-?)(\\b0[xX][a-fA-F0-9']+|(\\b[\\d']+(\\.[\\d']*)?|\\.[\\d']+)([eE][-+]?[\\d']+)?)"}],r:0},i={cN:"meta",b:/#\s*[a-z]+\b/,e:/$/,k:{"meta-keyword":"if else elif endif define undef warning error line pragma ifdef ifndef include"},c:[{b:/\\\n/,r:0},t.inherit(r,{cN:"meta-string"}),{cN:"meta-string",b:/<[^\n>]*>/,e:/$/,i:"\\n"},t.CLCM,t.CBCM]},a=t.IR+"\\s*\\(",c={keyword:"int float while private char catch import module export virtual operator sizeof dynamic_cast|10 typedef const_cast|10 const for static_cast|10 union namespace unsigned long volatile static protected bool template mutable if public friend do goto auto void enum else break extern using asm case typeid short reinterpret_cast|10 default double register explicit signed typename try this switch continue inline delete alignof constexpr decltype noexcept static_assert thread_local restrict _Bool complex _Complex _Imaginary atomic_bool atomic_char atomic_schar atomic_uchar atomic_short atomic_ushort atomic_int atomic_uint atomic_long atomic_ulong atomic_llong atomic_ullong new throw return and or not",built_in:"std string cin cout cerr clog stdin stdout stderr stringstream istringstream ostringstream auto_ptr deque list queue stack vector map set bitset multiset multimap unordered_set unordered_map unordered_multiset unordered_multimap array shared_ptr abort abs acos asin atan2 atan calloc ceil cosh cos exit exp fabs floor fmod fprintf fputs free frexp fscanf isalnum isalpha iscntrl isdigit isgraph islower isprint ispunct isspace isupper isxdigit tolower toupper labs ldexp log10 log malloc realloc memchr memcmp memcpy memset modf pow printf putchar puts scanf sinh sin snprintf sprintf sqrt sscanf strcat strchr strcmp strcpy strcspn strlen strncat strncmp strncpy strpbrk strrchr strspn strstr tanh tan vfprintf vprintf vsprintf endl initializer_list unique_ptr",literal:"true false nullptr NULL"},n=[e,t.CLCM,t.CBCM,s,r];return{aliases:["c","cc","h","c++","h++","hpp"],k:c,i:"</",c:n.concat([i,{b:"\\b(deque|list|queue|stack|vector|map|set|bitset|multiset|multimap|unordered_map|unordered_set|unordered_multiset|unordered_multimap|array)\\s*<",e:">",k:c,c:["self",e]},{b:t.IR+"::",k:c},{v:[{b:/=/,e:/;/},{b:/\(/,e:/\)/},{bK:"new throw return else",e:/;/}],k:c,c:n.concat([{b:/\(/,e:/\)/,k:c,c:n.concat(["self"]),r:0}]),r:0},{cN:"function",b:"("+t.IR+"[\\*&\\s]+)+"+a,rB:!0,e:/[{;=]/,eE:!0,k:c,i:/[^\w\s\*&]/,c:[{b:a,rB:!0,c:[t.TM],r:0},{cN:"params",b:/\(/,e:/\)/,k:c,r:0,c:[t.CLCM,t.CBCM,r,s,e]},t.CLCM,t.CBCM,i]},{cN:"class",bK:"class struct",e:/[{;:]/,c:[{b:/</,e:/>/,c:["self"]},t.TM]}]),exports:{preprocessor:i,strings:r,k:c}}});hljs.registerLanguage("ruby",function(e){var b="[a-zA-Z_]\\w*[!?=]?|[-+~]\\@|<<|>>|=~|===?|<=>|[<>]=?|\\*\\*|[-/+%^&*~`|]|\\[\\]=?",r={keyword:"and then defined module in return redo if BEGIN retry end for self when next until do begin unless END rescue else break undef not super class case require yield alias while ensure elsif or include attr_reader attr_writer attr_accessor",literal:"true false nil"},c={cN:"doctag",b:"@[A-Za-z]+"},a={b:"#<",e:">"},s=[e.C("#","$",{c:[c]}),e.C("^\\=begin","^\\=end",{c:[c],r:10}),e.C("^__END__","\\n$")],n={cN:"subst",b:"#\\{",e:"}",k:r},t={cN:"string",c:[e.BE,n],v:[{b:/'/,e:/'/},{b:/"/,e:/"/},{b:/`/,e:/`/},{b:"%[qQwWx]?\\(",e:"\\)"},{b:"%[qQwWx]?\\[",e:"\\]"},{b:"%[qQwWx]?{",e:"}"},{b:"%[qQwWx]?<",e:">"},{b:"%[qQwWx]?/",e:"/"},{b:"%[qQwWx]?%",e:"%"},{b:"%[qQwWx]?-",e:"-"},{b:"%[qQwWx]?\\|",e:"\\|"},{b:/\B\?(\\\d{1,3}|\\x[A-Fa-f0-9]{1,2}|\\u[A-Fa-f0-9]{4}|\\?\S)\b/},{b:/<<(-?)\w+$/,e:/^\s*\w+$/}]},i={cN:"params",b:"\\(",e:"\\)",endsParent:!0,k:r},d=[t,a,{cN:"class",bK:"class module",e:"$|;",i:/=/,c:[e.inherit(e.TM,{b:"[A-Za-z_]\\w*(::\\w+)*(\\?|\\!)?"}),{b:"<\\s*",c:[{b:"("+e.IR+"::)?"+e.IR}]}].concat(s)},{cN:"function",bK:"def",e:"$|;",c:[e.inherit(e.TM,{b:b}),i].concat(s)},{b:e.IR+"::"},{cN:"symbol",b:e.UIR+"(\\!|\\?)?:",r:0},{cN:"symbol",b:":(?!\\s)",c:[t,{b:b}],r:0},{cN:"number",b:"(\\b0[0-7_]+)|(\\b0x[0-9a-fA-F_]+)|(\\b[1-9][0-9_]*(\\.[0-9_]+)?)|[0_]\\b",r:0},{b:"(\\$\\W)|((\\$|\\@\\@?)(\\w+))"},{cN:"params",b:/\|/,e:/\|/,k:r},{b:"("+e.RSR+"|unless)\\s*",k:"unless",c:[a,{cN:"regexp",c:[e.BE,n],i:/\n/,v:[{b:"/",e:"/[a-z]*"},{b:"%r{",e:"}[a-z]*"},{b:"%r\\(",e:"\\)[a-z]*"},{b:"%r!",e:"![a-z]*"},{b:"%r\\[",e:"\\][a-z]*"}]}].concat(s),r:0}].concat(s);n.c=d,i.c=d;var l="[>?]>",o="[\\w#]+\\(\\w+\\):\\d+:\\d+>",u="(\\w+-)?\\d+\\.\\d+\\.\\d(p\\d+)?[^>]+>",w=[{b:/^\s*=>/,starts:{e:"$",c:d}},{cN:"meta",b:"^("+l+"|"+o+"|"+u+")",starts:{e:"$",c:d}}];return{aliases:["rb","gemspec","podspec","thor","irb"],k:r,i:/\/\*/,c:s.concat(w).concat(d)}});hljs.registerLanguage("yaml",function(e){var b="true false yes no null",a="^[ \\-]*",r="[a-zA-Z_][\\w\\-]*",t={cN:"attr",v:[{b:a+r+":"},{b:a+'"'+r+'":'},{b:a+"'"+r+"':"}]},c={cN:"template-variable",v:[{b:"{{",e:"}}"},{b:"%{",e:"}"}]},l={cN:"string",r:0,v:[{b:/'/,e:/'/},{b:/"/,e:/"/},{b:/\S+/}],c:[e.BE,c]};return{cI:!0,aliases:["yml","YAML","yaml"],c:[t,{cN:"meta",b:"^---s*$",r:10},{cN:"string",b:"[\\|>] *$",rE:!0,c:l.c,e:t.v[0].b},{b:"<%[%=-]?",e:"[%-]?%>",sL:"ruby",eB:!0,eE:!0,r:0},{cN:"type",b:"!!"+e.UIR},{cN:"meta",b:"&"+e.UIR+"$"},{cN:"meta",b:"\\*"+e.UIR+"$"},{cN:"bullet",b:"^ *-",r:0},e.HCM,{bK:b,k:{literal:b}},e.CNM,l]}});hljs.registerLanguage("css",function(e){var c="[a-zA-Z-][a-zA-Z0-9_-]*",t={b:/[A-Z\_\.\-]+\s*:/,rB:!0,e:";",eW:!0,c:[{cN:"attribute",b:/\S/,e:":",eE:!0,starts:{eW:!0,eE:!0,c:[{b:/[\w-]+\(/,rB:!0,c:[{cN:"built_in",b:/[\w-]+/},{b:/\(/,e:/\)/,c:[e.ASM,e.QSM]}]},e.CSSNM,e.QSM,e.ASM,e.CBCM,{cN:"number",b:"#[0-9A-Fa-f]+"},{cN:"meta",b:"!important"}]}}]};return{cI:!0,i:/[=\/|'\$]/,c:[e.CBCM,{cN:"selector-id",b:/#[A-Za-z0-9_-]+/},{cN:"selector-class",b:/\.[A-Za-z0-9_-]+/},{cN:"selector-attr",b:/\[/,e:/\]/,i:"$"},{cN:"selector-pseudo",b:/:(:)?[a-zA-Z0-9\_\-\+\(\)"'.]+/},{b:"@(font-face|page)",l:"[a-z-]+",k:"font-face page"},{b:"@",e:"[{;]",i:/:/,c:[{cN:"keyword",b:/\w+/},{b:/\s/,eW:!0,eE:!0,r:0,c:[e.ASM,e.QSM,e.CSSNM]}]},{cN:"selector-tag",b:c,r:0},{b:"{",e:"}",i:/\S/,c:[e.CBCM,t]}]}});hljs.registerLanguage("fortran",function(e){var t={cN:"params",b:"\\(",e:"\\)"},n={literal:".False. .True.",keyword:"kind do while private call intrinsic where elsewhere type endtype endmodule endselect endinterface end enddo endif if forall endforall only contains default return stop then public subroutine|10 function program .and. .or. .not. .le. .eq. .ge. .gt. .lt. goto save else use module select case access blank direct exist file fmt form formatted iostat name named nextrec number opened rec recl sequential status unformatted unit continue format pause cycle exit c_null_char c_alert c_backspace c_form_feed flush wait decimal round iomsg synchronous nopass non_overridable pass protected volatile abstract extends import non_intrinsic value deferred generic final enumerator class associate bind enum c_int c_short c_long c_long_long c_signed_char c_size_t c_int8_t c_int16_t c_int32_t c_int64_t c_int_least8_t c_int_least16_t c_int_least32_t c_int_least64_t c_int_fast8_t c_int_fast16_t c_int_fast32_t c_int_fast64_t c_intmax_t C_intptr_t c_float c_double c_long_double c_float_complex c_double_complex c_long_double_complex c_bool c_char c_null_ptr c_null_funptr c_new_line c_carriage_return c_horizontal_tab c_vertical_tab iso_c_binding c_loc c_funloc c_associated  c_f_pointer c_ptr c_funptr iso_fortran_env character_storage_size error_unit file_storage_size input_unit iostat_end iostat_eor numeric_storage_size output_unit c_f_procpointer ieee_arithmetic ieee_support_underflow_control ieee_get_underflow_mode ieee_set_underflow_mode newunit contiguous recursive pad position action delim readwrite eor advance nml interface procedure namelist include sequence elemental pure integer real character complex logical dimension allocatable|10 parameter external implicit|10 none double precision assign intent optional pointer target in out common equivalence data",built_in:"alog alog10 amax0 amax1 amin0 amin1 amod cabs ccos cexp clog csin csqrt dabs dacos dasin datan datan2 dcos dcosh ddim dexp dint dlog dlog10 dmax1 dmin1 dmod dnint dsign dsin dsinh dsqrt dtan dtanh float iabs idim idint idnint ifix isign max0 max1 min0 min1 sngl algama cdabs cdcos cdexp cdlog cdsin cdsqrt cqabs cqcos cqexp cqlog cqsin cqsqrt dcmplx dconjg derf derfc dfloat dgamma dimag dlgama iqint qabs qacos qasin qatan qatan2 qcmplx qconjg qcos qcosh qdim qerf qerfc qexp qgamma qimag qlgama qlog qlog10 qmax1 qmin1 qmod qnint qsign qsin qsinh qsqrt qtan qtanh abs acos aimag aint anint asin atan atan2 char cmplx conjg cos cosh exp ichar index int log log10 max min nint sign sin sinh sqrt tan tanh print write dim lge lgt lle llt mod nullify allocate deallocate adjustl adjustr all allocated any associated bit_size btest ceiling count cshift date_and_time digits dot_product eoshift epsilon exponent floor fraction huge iand ibclr ibits ibset ieor ior ishft ishftc lbound len_trim matmul maxexponent maxloc maxval merge minexponent minloc minval modulo mvbits nearest pack present product radix random_number random_seed range repeat reshape rrspacing scale scan selected_int_kind selected_real_kind set_exponent shape size spacing spread sum system_clock tiny transpose trim ubound unpack verify achar iachar transfer dble entry dprod cpu_time command_argument_count get_command get_command_argument get_environment_variable is_iostat_end ieee_arithmetic ieee_support_underflow_control ieee_get_underflow_mode ieee_set_underflow_mode is_iostat_eor move_alloc new_line selected_char_kind same_type_as extends_type_ofacosh asinh atanh bessel_j0 bessel_j1 bessel_jn bessel_y0 bessel_y1 bessel_yn erf erfc erfc_scaled gamma log_gamma hypot norm2 atomic_define atomic_ref execute_command_line leadz trailz storage_size merge_bits bge bgt ble blt dshiftl dshiftr findloc iall iany iparity image_index lcobound ucobound maskl maskr num_images parity popcnt poppar shifta shiftl shiftr this_image"};return{cI:!0,aliases:["f90","f95"],k:n,i:/\/\*/,c:[e.inherit(e.ASM,{cN:"string",r:0}),e.inherit(e.QSM,{cN:"string",r:0}),{cN:"function",bK:"subroutine function program",i:"[${=\\n]",c:[e.UTM,t]},e.C("!","$",{r:0}),{cN:"number",b:"(?=\\b|\\+|\\-|\\.)(?=\\.\\d|\\d)(?:\\d+)?(?:\\.?\\d*)(?:[de][+-]?\\d+)?\\b\\.?",r:0}]}});hljs.registerLanguage("awk",function(e){var r={cN:"variable",v:[{b:/\$[\w\d#@][\w\d_]*/},{b:/\$\{(.*?)}/}]},b="BEGIN END if else while do for in break continue delete next nextfile function func exit|10",n={cN:"string",c:[e.BE],v:[{b:/(u|b)?r?'''/,e:/'''/,r:10},{b:/(u|b)?r?"""/,e:/"""/,r:10},{b:/(u|r|ur)'/,e:/'/,r:10},{b:/(u|r|ur)"/,e:/"/,r:10},{b:/(b|br)'/,e:/'/},{b:/(b|br)"/,e:/"/},e.ASM,e.QSM]};return{k:{keyword:b},c:[r,n,e.RM,e.HCM,e.NM]}});hljs.registerLanguage("makefile",function(e){var i={cN:"variable",v:[{b:"\\$\\("+e.UIR+"\\)",c:[e.BE]},{b:/\$[@%<?\^\+\*]/}]},r={cN:"string",b:/"/,e:/"/,c:[e.BE,i]},a={cN:"variable",b:/\$\([\w-]+\s/,e:/\)/,k:{built_in:"subst patsubst strip findstring filter filter-out sort word wordlist firstword lastword dir notdir suffix basename addsuffix addprefix join wildcard realpath abspath error warning shell origin flavor foreach if or and call eval file value"},c:[i]},n={b:"^"+e.UIR+"\\s*[:+?]?=",i:"\\n",rB:!0,c:[{b:"^"+e.UIR,e:"[:+?]?=",eE:!0}]},t={cN:"meta",b:/^\.PHONY:/,e:/$/,k:{"meta-keyword":".PHONY"},l:/[\.\w]+/},l={cN:"section",b:/^[^\s]+:/,e:/$/,c:[i]};return{aliases:["mk","mak"],k:"define endef undefine ifdef ifndef ifeq ifneq else endif include -include sinclude override export unexport private vpath",l:/[\w-]+/,c:[e.HCM,i,r,a,n,t,l]}});hljs.registerLanguage("java",function(e){var a="[À-ʸa-zA-Z_$][À-ʸa-zA-Z_$0-9]*",t=a+"(<"+a+"(\\s*,\\s*"+a+")*>)?",r="false synchronized int abstract float private char boolean static null if const for true while long strictfp finally protected import native final void enum else break transient catch instanceof byte super volatile case assert short package default double public try this switch continue throws protected public private module requires exports do",s="\\b(0[bB]([01]+[01_]+[01]+|[01]+)|0[xX]([a-fA-F0-9]+[a-fA-F0-9_]+[a-fA-F0-9]+|[a-fA-F0-9]+)|(([\\d]+[\\d_]+[\\d]+|[\\d]+)(\\.([\\d]+[\\d_]+[\\d]+|[\\d]+))?|\\.([\\d]+[\\d_]+[\\d]+|[\\d]+))([eE][-+]?\\d+)?)[lLfF]?",c={cN:"number",b:s,r:0};return{aliases:["jsp"],k:r,i:/<\/|#/,c:[e.C("/\\*\\*","\\*/",{r:0,c:[{b:/\w+@/,r:0},{cN:"doctag",b:"@[A-Za-z]+"}]}),e.CLCM,e.CBCM,e.ASM,e.QSM,{cN:"class",bK:"class interface",e:/[{;=]/,eE:!0,k:"class interface",i:/[:"\[\]]/,c:[{bK:"extends implements"},e.UTM]},{bK:"new throw return else",r:0},{cN:"function",b:"("+t+"\\s+)+"+e.UIR+"\\s*\\(",rB:!0,e:/[{;=]/,eE:!0,k:r,c:[{b:e.UIR+"\\s*\\(",rB:!0,r:0,c:[e.UTM]},{cN:"params",b:/\(/,e:/\)/,k:r,r:0,c:[e.ASM,e.QSM,e.CNM,e.CBCM]},e.CLCM,e.CBCM]},c,{cN:"meta",b:"@[A-Za-z]+"}]}});hljs.registerLanguage("stan",function(e){return{c:[e.HCM,e.CLCM,e.CBCM,{b:e.UIR,l:e.UIR,k:{name:"for in while repeat until if then else",symbol:"bernoulli bernoulli_logit binomial binomial_logit beta_binomial hypergeometric categorical categorical_logit ordered_logistic neg_binomial neg_binomial_2 neg_binomial_2_log poisson poisson_log multinomial normal exp_mod_normal skew_normal student_t cauchy double_exponential logistic gumbel lognormal chi_square inv_chi_square scaled_inv_chi_square exponential inv_gamma weibull frechet rayleigh wiener pareto pareto_type_2 von_mises uniform multi_normal multi_normal_prec multi_normal_cholesky multi_gp multi_gp_cholesky multi_student_t gaussian_dlm_obs dirichlet lkj_corr lkj_corr_cholesky wishart inv_wishart","selector-tag":"int real vector simplex unit_vector ordered positive_ordered row_vector matrix cholesky_factor_corr cholesky_factor_cov corr_matrix cov_matrix",title:"functions model data parameters quantities transformed generated",literal:"true false"},r:0},{cN:"number",b:"0[xX][0-9a-fA-F]+[Li]?\\b",r:0},{cN:"number",b:"0[xX][0-9a-fA-F]+[Li]?\\b",r:0},{cN:"number",b:"\\d+(?:[eE][+\\-]?\\d*)?L\\b",r:0},{cN:"number",b:"\\d+\\.(?!\\d)(?:i\\b)?",r:0},{cN:"number",b:"\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",r:0},{cN:"number",b:"\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",r:0}]}});hljs.registerLanguage("javascript",function(e){var r="[A-Za-z$_][0-9A-Za-z$_]*",t={keyword:"in of if for while finally var new function do return void else break catch instanceof with throw case default try this switch continue typeof delete let yield const export super debugger as async await static import from as",literal:"true false null undefined NaN Infinity",built_in:"eval isFinite isNaN parseFloat parseInt decodeURI decodeURIComponent encodeURI encodeURIComponent escape unescape Object Function Boolean Error EvalError InternalError RangeError ReferenceError StopIteration SyntaxError TypeError URIError Number Math Date String RegExp Array Float32Array Float64Array Int16Array Int32Array Int8Array Uint16Array Uint32Array Uint8Array Uint8ClampedArray ArrayBuffer DataView JSON Intl arguments require module console window document Symbol Set Map WeakSet WeakMap Proxy Reflect Promise"},a={cN:"number",v:[{b:"\\b(0[bB][01]+)"},{b:"\\b(0[oO][0-7]+)"},{b:e.CNR}],r:0},n={cN:"subst",b:"\\$\\{",e:"\\}",k:t,c:[]},c={cN:"string",b:"`",e:"`",c:[e.BE,n]};n.c=[e.ASM,e.QSM,c,a,e.RM];var s=n.c.concat([e.CBCM,e.CLCM]);return{aliases:["js","jsx"],k:t,c:[{cN:"meta",r:10,b:/^\s*['"]use (strict|asm)['"]/},{cN:"meta",b:/^#!/,e:/$/},e.ASM,e.QSM,c,e.CLCM,e.CBCM,a,{b:/[{,]\s*/,r:0,c:[{b:r+"\\s*:",rB:!0,r:0,c:[{cN:"attr",b:r,r:0}]}]},{b:"("+e.RSR+"|\\b(case|return|throw)\\b)\\s*",k:"return throw case",c:[e.CLCM,e.CBCM,e.RM,{cN:"function",b:"(\\(.*?\\)|"+r+")\\s*=>",rB:!0,e:"\\s*=>",c:[{cN:"params",v:[{b:r},{b:/\(\s*\)/},{b:/\(/,e:/\)/,eB:!0,eE:!0,k:t,c:s}]}]},{b:/</,e:/(\/\w+|\w+\/)>/,sL:"xml",c:[{b:/<\w+\s*\/>/,skip:!0},{b:/<\w+/,e:/(\/\w+|\w+\/)>/,skip:!0,c:[{b:/<\w+\s*\/>/,skip:!0},"self"]}]}],r:0},{cN:"function",bK:"function",e:/\{/,eE:!0,c:[e.inherit(e.TM,{b:r}),{cN:"params",b:/\(/,e:/\)/,eB:!0,eE:!0,c:s}],i:/\[|%/},{b:/\$[(.]/},e.METHOD_GUARD,{cN:"class",bK:"class",e:/[{;=]/,eE:!0,i:/[:"\[\]]/,c:[{bK:"extends"},e.UTM]},{bK:"constructor",e:/\{/,eE:!0}],i:/#(?!!)/}});hljs.registerLanguage("tex",function(c){var e={cN:"tag",b:/\\/,r:0,c:[{cN:"name",v:[{b:/[a-zA-Zа-яА-я]+[*]?/},{b:/[^a-zA-Zа-яА-я0-9]/}],starts:{eW:!0,r:0,c:[{cN:"string",v:[{b:/\[/,e:/\]/},{b:/\{/,e:/\}/}]},{b:/\s*=\s*/,eW:!0,r:0,c:[{cN:"number",b:/-?\d*\.?\d+(pt|pc|mm|cm|in|dd|cc|ex|em)?/}]}]}}]};return{c:[e,{cN:"formula",c:[e],r:0,v:[{b:/\$\$/,e:/\$\$/},{b:/\$/,e:/\$/}]},c.C("%","$",{r:0})]}});hljs.registerLanguage("xml",function(s){var e="[A-Za-z0-9\\._:-]+",t={eW:!0,i:/</,r:0,c:[{cN:"attr",b:e,r:0},{b:/=\s*/,r:0,c:[{cN:"string",endsParent:!0,v:[{b:/"/,e:/"/},{b:/'/,e:/'/},{b:/[^\s"'=<>`]+/}]}]}]};return{aliases:["html","xhtml","rss","atom","xjb","xsd","xsl","plist"],cI:!0,c:[{cN:"meta",b:"<!DOCTYPE",e:">",r:10,c:[{b:"\\[",e:"\\]"}]},s.C("<!--","-->",{r:10}),{b:"<\\!\\[CDATA\\[",e:"\\]\\]>",r:10},{b:/<\?(php)?/,e:/\?>/,sL:"php",c:[{b:"/\\*",e:"\\*/",skip:!0}]},{cN:"tag",b:"<style(?=\\s|>|$)",e:">",k:{name:"style"},c:[t],starts:{e:"</style>",rE:!0,sL:["css","xml"]}},{cN:"tag",b:"<script(?=\\s|>|$)",e:">",k:{name:"script"},c:[t],starts:{e:"</script>",rE:!0,sL:["actionscript","javascript","handlebars","xml"]}},{cN:"meta",v:[{b:/<\?xml/,e:/\?>/,r:10},{b:/<\?\w+/,e:/\?>/}]},{cN:"tag",b:"</?",e:"/?>",c:[{cN:"name",b:/[^\/><\s]+/,r:0},t]}]}});hljs.registerLanguage("markdown",function(e){return{aliases:["md","mkdown","mkd"],c:[{cN:"section",v:[{b:"^#{1,6}",e:"$"},{b:"^.+?\\n[=-]{2,}$"}]},{b:"<",e:">",sL:"xml",r:0},{cN:"bullet",b:"^([*+-]|(\\d+\\.))\\s+"},{cN:"strong",b:"[*_]{2}.+?[*_]{2}"},{cN:"emphasis",v:[{b:"\\*.+?\\*"},{b:"_.+?_",r:0}]},{cN:"quote",b:"^>\\s+",e:"$"},{cN:"code",v:[{b:"^```w*s*$",e:"^```s*$"},{b:"`.+?`"},{b:"^( {4}|	)",e:"$",r:0}]},{b:"^[-\\*]{3,}",e:"$"},{b:"\\[.+?\\][\\(\\[].*?[\\)\\]]",rB:!0,c:[{cN:"string",b:"\\[",e:"\\]",eB:!0,rE:!0,r:0},{cN:"link",b:"\\]\\(",e:"\\)",eB:!0,eE:!0},{cN:"symbol",b:"\\]\\[",e:"\\]",eB:!0,eE:!0}],r:10},{b:/^\[[^\n]+\]:/,rB:!0,c:[{cN:"symbol",b:/\[/,e:/\]/,eB:!0,eE:!0},{cN:"link",b:/:\s*/,e:/$/,eB:!0}]}]}});hljs.registerLanguage("json",function(e){var i={literal:"true false null"},n=[e.QSM,e.CNM],r={e:",",eW:!0,eE:!0,c:n,k:i},t={b:"{",e:"}",c:[{cN:"attr",b:/"/,e:/"/,c:[e.BE],i:"\\n"},e.inherit(r,{b:/:/})],i:"\\S"},c={b:"\\[",e:"\\]",c:[e.inherit(r)],i:"\\S"};return n.splice(n.length,0,t,c),{c:n,k:i,i:"\\S"}});"></script>

<style type="text/css">
code{white-space: pre-wrap;}
span.smallcaps{font-variant: small-caps;}
span.underline{text-decoration: underline;}
div.column{display: inline-block; vertical-align: top; width: 50%;}
div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
ul.task-list{list-style: none;}
</style>

<style type="text/css">code{white-space: pre;}</style>
<script type="text/javascript">
if (window.hljs) {
  hljs.configure({languages: []});
  hljs.initHighlightingOnLoad();
  if (document.readyState && document.readyState === "complete") {
    window.setTimeout(function() { hljs.initHighlighting(); }, 0);
  }
}
</script>









<style type="text/css">
.main-container {
max-width: 940px;
margin-left: auto;
margin-right: auto;
}
img {
max-width:100%;
}
.tabbed-pane {
padding-top: 12px;
}
.html-widget {
margin-bottom: 20px;
}
button.code-folding-btn:focus {
outline: none;
}
summary {
display: list-item;
}
details > summary > p:only-child {
display: inline;
}
pre code {
padding: 0;
}
</style>



<!-- tabsets -->

<style type="text/css">
.tabset-dropdown > .nav-tabs {
display: inline-table;
max-height: 500px;
min-height: 44px;
overflow-y: auto;
border: 1px solid #ddd;
border-radius: 4px;
}
.tabset-dropdown > .nav-tabs > li.active:before, .tabset-dropdown > .nav-tabs.nav-tabs-open:before {
content: "\e259";
font-family: 'Glyphicons Halflings';
display: inline-block;
padding: 10px;
border-right: 1px solid #ddd;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before {
content: "\e258";
font-family: 'Glyphicons Halflings';
border: none;
}
.tabset-dropdown > .nav-tabs > li.active {
display: block;
}
.tabset-dropdown > .nav-tabs > li > a,
.tabset-dropdown > .nav-tabs > li > a:focus,
.tabset-dropdown > .nav-tabs > li > a:hover {
border: none;
display: inline-block;
border-radius: 4px;
background-color: transparent;
}
.tabset-dropdown > .nav-tabs.nav-tabs-open > li {
display: block;
float: none;
}
.tabset-dropdown > .nav-tabs > li {
display: none;
}
</style>

<!-- code folding -->



<style type="text/css">
#TOC {
margin: 25px 0px 20px 0px;
}
@media (max-width: 768px) {
#TOC {
position: relative;
width: 100%;
}
}
@media print {
.toc-content {

float: right;
}
}
.toc-content {
padding-left: 30px;
padding-right: 40px;
}
div.main-container {
max-width: 1200px;
}
div.tocify {
width: 20%;
max-width: 260px;
max-height: 85%;
}
@media (min-width: 768px) and (max-width: 991px) {
div.tocify {
width: 25%;
}
}
@media (max-width: 767px) {
div.tocify {
width: 100%;
max-width: none;
}
}
.tocify ul, .tocify li {
line-height: 20px;
}
.tocify-subheader .tocify-item {
font-size: 0.90em;
}
.tocify .list-group-item {
border-radius: 0px;
}
</style>



</head>

<body>


<div class="container-fluid main-container">


<!-- setup 3col/9col grid for toc_float and main content  -->
<div class="row">
<div class="col-xs-12 col-sm-4 col-md-3">
<div id="TOC" class="tocify">
</div>
</div>

<div class="toc-content col-xs-12 col-sm-8 col-md-9">




<div id="header">



<h1 class="title toc-ignore">corrections_merged</h1>

</div>


<div id="hypotheses" class="section level2">
<h2>Hypotheses</h2>
</div>
<div id="h1a" class="section level2">
<h2>H1a</h2>
<div id="models" class="section level3">
<h3>Models</h3>
<pre class="r"><code>h1a_all &lt;- lmer(DV ~ condition + country + (1|ResponseId)+(1|post:country), data=corrections_all_long)
summ(h1a_all, digits=3, confint=T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 24000
## Dependent Variable: DV
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 58146.108, BIC = 58210.795
## Pseudo-R² (fixed effects) = 0.136
## Pseudo-R² (total) = 0.589 
## 
## FIXED EFFECTS:
## --------------------------------------------------------------------------------
##                               Est.     2.5%    97.5%   t val.       d.f.       p
## ------------------------- -------- -------- -------- -------- ---------- -------
## (Intercept)                  0.863    0.660    1.066    8.335     24.733   0.000
## conditioncorrection         -0.061   -0.126    0.003   -1.860   2995.006   0.063
## conditionlink               -0.102   -0.166   -0.038   -3.123   2995.006   0.002
## countryIndia                 0.753    0.471    1.035    5.235     23.067   0.000
## countryUK                   -0.184   -0.466    0.098   -1.281     23.067   0.213
## --------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.689   
##  post:country   (Intercept)     0.280   
##    Residual                     0.708   
## ----------------------------------------
## 
## Grouping variables:
## ---------------------------------
##     Group       # groups    ICC  
## -------------- ---------- -------
##   ResponseId      3000     0.450 
##  post:country      24      0.074 
## ---------------------------------</code></pre>
<pre class="r"><code>h1a_uk &lt;- lmer(accuracy ~ condition + post + (1|ResponseId), data=subset(corrections_accuracy_long, country==&quot;UK&quot;))
summ(h1a_uk, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9393.685, BIC = 9444.038
## Pseudo-R² (fixed effects) = 0.046
## Pseudo-R² (total) = 0.462 
## 
## FIXED EFFECTS:
## ----------------------------------------------------------------------------------
##                                Est.     2.5%    97.5%    t val.       d.f.       p
## -------------------------- -------- -------- -------- --------- ---------- -------
## (Intercept)                   0.865    0.787    0.944    21.535   1519.633   0.000
## conditioncorrection          -0.010   -0.111    0.091    -0.198    997.000   0.843
## conditionlink                -0.071   -0.170    0.029    -1.392    997.000   0.164
## postfalse_2_accuracy         -0.304   -0.361   -0.247   -10.408   2997.000   0.000
## postfalse_3_accuracy         -0.078   -0.135   -0.021    -2.670   2997.000   0.008
## postfalse_4_accuracy          0.226    0.169    0.283     7.737   2997.000   0.000
## ----------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.574   
##   Residual                    0.653   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.436 
## -------------------------------</code></pre>
<pre class="r"><code>model_summary &lt;- summary(h1a_uk)
coefs &lt;- fixef(h1a_uk)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##          (Intercept)  conditioncorrection        conditionlink 
##               0.0000            -101.1798            -108.1535 
## postfalse_2_accuracy postfalse_3_accuracy postfalse_4_accuracy 
##            -135.1279            -109.0131             -73.8852</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_uk)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##          (Intercept)  conditioncorrection        conditionlink 
##           28.8469832           -0.3403373           -2.3520514 
## postfalse_2_accuracy postfalse_3_accuracy postfalse_4_accuracy 
##          -10.1333333           -2.6000000            7.5333333</code></pre>
<pre class="r"><code>h1a_brazil &lt;- lmer(accuracy ~ condition +  post +(1|ResponseId), data=subset(corrections_accuracy_long, country==&quot;Brazil&quot;))
summ(h1a_brazil, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10893.943, BIC = 10944.295
## Pseudo-R² (fixed effects) = 0.078
## Pseudo-R² (total) = 0.330 
## 
## FIXED EFFECTS:
## ----------------------------------------------------------------------------------
##                                Est.     2.5%    97.5%    t val.       d.f.       p
## -------------------------- -------- -------- -------- --------- ---------- -------
## (Intercept)                   1.445    1.361    1.530    33.367   1832.920   0.000
## conditioncorrection          -0.083   -0.184    0.018    -1.606    997.000   0.109
## conditionlink                -0.100   -0.201    0.001    -1.933    997.000   0.053
## postfalse_2_accuracy         -0.501   -0.574   -0.428   -13.373   2997.000   0.000
## postfalse_3_accuracy         -0.783   -0.856   -0.710   -20.901   2997.000   0.000
## postfalse_4_accuracy         -0.363   -0.436   -0.290    -9.690   2997.000   0.000
## ----------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.515   
##   Residual                    0.838   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.274 
## -------------------------------</code></pre>
<pre class="r"><code>model_summary &lt;- summary(h1a_brazil)

coefs &lt;- fixef(h1a_brazil)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##          (Intercept)  conditioncorrection        conditionlink 
##               0.0000            -105.7316            -106.8884 
## postfalse_2_accuracy postfalse_3_accuracy postfalse_4_accuracy 
##            -134.6595            -154.1684            -125.1126</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_brazil)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##          (Intercept)  conditioncorrection        conditionlink 
##            48.183078            -2.761649            -3.319024 
## postfalse_2_accuracy postfalse_3_accuracy postfalse_4_accuracy 
##           -16.700000           -26.100000           -12.100000</code></pre>
<pre class="r"><code>h1a_india &lt;- lmer(accuracy ~ condition + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;India&quot;))
summ(h1a_india, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 11027.932, BIC = 11078.285
## Pseudo-R² (fixed effects) = 0.078
## Pseudo-R² (total) = 0.540 
## 
## FIXED EFFECTS:
## ---------------------------------------------------------------------------------
##                                Est.     2.5%    97.5%   t val.       d.f.       p
## -------------------------- -------- -------- -------- -------- ---------- -------
## (Intercept)                   1.519    1.415    1.622   28.825   1411.714   0.000
## conditioncorrection          -0.077   -0.209    0.056   -1.128    997.000   0.260
## conditionlink                -0.164   -0.297   -0.031   -2.415    997.000   0.016
## postfalse_2_accuracy          0.227    0.159    0.295    6.495   2997.000   0.000
## postfalse_3_accuracy         -0.226   -0.294   -0.158   -6.467   2997.000   0.000
## postfalse_4_accuracy          0.628    0.560    0.696   17.970   2997.000   0.000
## ---------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.782   
##   Residual                    0.781   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.501 
## -------------------------------</code></pre>
<pre class="r"><code>model_summary &lt;- summary(h1a_india)

coefs &lt;- fixef(h1a_india)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##          (Intercept)  conditioncorrection        conditionlink 
##              0.00000           -105.03809           -110.78804 
## postfalse_2_accuracy postfalse_3_accuracy postfalse_4_accuracy 
##            -85.05111           -114.88303            -58.64360</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_india)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##          (Intercept)  conditioncorrection        conditionlink 
##            50.616919            -2.550128            -5.460576 
## postfalse_2_accuracy postfalse_3_accuracy postfalse_4_accuracy 
##             7.566667            -7.533333            20.933333</code></pre>
</div>
<div id="plots" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>h1a_uk_results &lt;- ggpredict(h1a_uk, terms = c(&quot;condition&quot;))
h1a_brazil_results &lt;- ggpredict(h1a_brazil, terms = c(&quot;condition&quot;))
h1a_india_results &lt;- ggpredict(h1a_india, terms = c(&quot;condition&quot;))</code></pre>
<pre class="r"><code>h1a_uk_plot &lt;- ggplot(h1a_uk_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction&quot;,&quot;Correction\n + link&quot;)) +
    scale_y_continuous(limits = c(0,2), breaks = c(0,1,2),expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;)) +
  ylab(&quot;Accuracy&quot;) +
  xlab(&quot;&quot;) +
  ggtitle(&quot;UK&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;,
        plot.title = element_text(hjust = 0.5),
        axis.text.x = element_text(size=11),
        axis.text.y = element_text(size=10),
        axis.title.y = element_text(size=15,face=&quot;bold&quot;),
        title = element_text(size=12,face=&quot;bold&quot;))

h1a_brazil_plot &lt;- ggplot(h1a_brazil_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction&quot;,&quot;Correction\n + link&quot;)) +
  scale_y_continuous(limits = c(0,2), breaks = c(0,1,2),expand = c(0,0)) +
  ylab(&quot;Accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Brazil&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.title.x=element_text(size=14,face=&quot;bold&quot;),
        axis.text.y=element_blank(),
        axis.text.x = element_text(size=11),
        legend.position = &quot;none&quot;,
        plot.title = element_text(hjust = 0.5),
        title = element_text(size=12,face=&quot;bold&quot;))

h1a_india_plot &lt;- ggplot(h1a_india_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction&quot;,&quot;Correction\n + link&quot;)) +
  scale_y_continuous(limits = c(0,2),breaks = c(0,1,2), expand = c(0,0)) +
  ylab(&quot;Accuracy&quot;) +
  xlab(&quot;&quot;) +
  ggtitle(&quot;India&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.text.x = element_text(size=11),
        axis.title.x=element_blank(),
        legend.position = &quot;none&quot;,
        plot.title = element_text(hjust = 0.5),
        title = element_text(size=12,face=&quot;bold&quot;))</code></pre>
</div>
</div>
<div id="h1b" class="section level2">
<h2>H1b</h2>
<div id="models-1" class="section level3">
<h3>Models</h3>
<pre class="r"><code>h1b_all &lt;- lmer(sharing ~ condition + (1 | ResponseId) +(1|post:country), data=corrections_sharing_long)
summ(h1b_all, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 12000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 29002.641, BIC = 29046.997
## Pseudo-R² (fixed effects) = 0.001
## Pseudo-R² (total) = 0.671 
## 
## FIXED EFFECTS:
## --------------------------------------------------------------------------------
##                               Est.     2.5%    97.5%   t val.       d.f.       p
## ------------------------- -------- -------- -------- -------- ---------- -------
## (Intercept)                  0.927    0.630    1.223    6.130     11.466   0.000
## conditioncorrection         -0.066   -0.138    0.006   -1.796   2994.863   0.073
## conditionlink               -0.093   -0.165   -0.022   -2.565   2994.853   0.010
## --------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.751   
##  post:country   (Intercept)     0.516   
##    Residual                     0.638   
## ----------------------------------------
## 
## Grouping variables:
## ---------------------------------
##     Group       # groups    ICC  
## -------------- ---------- -------
##   ResponseId      3000     0.456 
##  post:country      12      0.215 
## ---------------------------------</code></pre>
<pre class="r"><code>h1b_uk &lt;- lmer(sharing ~ condition + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;UK&quot;))
summ(h1b_uk, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 7146.206, BIC = 7196.559
## Pseudo-R² (fixed effects) = 0.002
## Pseudo-R² (total) = 0.712 
## 
## FIXED EFFECTS:
## --------------------------------------------------------------------------------
##                               Est.     2.5%    97.5%   t val.       d.f.       p
## ------------------------- -------- -------- -------- -------- ---------- -------
## (Intercept)                  0.492    0.412    0.572   12.002   1187.461   0.000
## conditioncorrection         -0.009   -0.119    0.101   -0.155    996.999   0.877
## conditionlink               -0.041   -0.149    0.067   -0.745    996.999   0.456
## postfalse_2_sharing         -0.083   -0.121   -0.045   -4.254   2997.000   0.000
## postfalse_3_sharing         -0.006   -0.044    0.032   -0.307   2997.000   0.758
## postfalse_4_sharing         -0.015   -0.053    0.023   -0.769   2997.000   0.442
## --------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.686   
##   Residual                    0.436   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.712 
## -------------------------------</code></pre>
<pre class="r"><code>model_summary &lt;- summary(h1b_uk)
coefs &lt;- fixef(h1b_uk)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink postfalse_2_sharing 
##              0.0000           -101.7708           -108.3696           -116.8742 
## postfalse_3_sharing postfalse_4_sharing 
##           -101.2198           -103.0496</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1b_uk)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink postfalse_2_sharing 
##          16.3958457          -0.2903421          -1.3722590          -2.7666667 
## postfalse_3_sharing postfalse_4_sharing 
##          -0.2000000          -0.5000000</code></pre>
<pre class="r"><code>h1b_brazil &lt;- lmer(sharing ~ condition + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;Brazil&quot;))
summ(h1b_brazil, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9951.107, BIC = 10001.460
## Pseudo-R² (fixed effects) = 0.026
## Pseudo-R² (total) = 0.504 
## 
## FIXED EFFECTS:
## ---------------------------------------------------------------------------------
##                               Est.     2.5%    97.5%    t val.       d.f.       p
## ------------------------- -------- -------- -------- --------- ---------- -------
## (Intercept)                  0.944    0.854    1.034    20.596   1420.137   0.000
## conditioncorrection         -0.115   -0.230    0.000    -1.955    997.000   0.051
## conditionlink               -0.070   -0.185    0.045    -1.197    997.000   0.232
## postfalse_2_sharing         -0.316   -0.376   -0.256   -10.306   2997.000   0.000
## postfalse_3_sharing         -0.397   -0.457   -0.337   -12.948   2997.000   0.000
## postfalse_4_sharing         -0.242   -0.302   -0.182    -7.893   2997.000   0.000
## ---------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.673   
##   Residual                    0.686   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.491 
## -------------------------------</code></pre>
<pre class="r"><code>model_summary &lt;- summary(h1b_brazil)
coefs &lt;- fixef(h1b_brazil)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink postfalse_2_sharing 
##              0.0000           -112.1520           -107.4307           -133.4650 
## postfalse_3_sharing postfalse_4_sharing 
##           -142.0430           -125.6282</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1b_brazil)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink postfalse_2_sharing 
##           31.475716           -3.824922           -2.338881          -10.533333 
## postfalse_3_sharing postfalse_4_sharing 
##          -13.233333           -8.066667</code></pre>
<pre class="r"><code>h1b_india &lt;- lmer(sharing ~ condition + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;India&quot;))
summ(h1b_india, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10948.938, BIC = 10999.291
## Pseudo-R² (fixed effects) = 0.046
## Pseudo-R² (total) = 0.597 
## 
## FIXED EFFECTS:
## --------------------------------------------------------------------------------
##                               Est.     2.5%    97.5%   t val.       d.f.       p
## ------------------------- -------- -------- -------- -------- ---------- -------
## (Intercept)                  1.466    1.355    1.576   26.021   1315.342   0.000
## conditioncorrection         -0.074   -0.219    0.071   -1.001    997.000   0.317
## conditionlink               -0.170   -0.315   -0.025   -2.304    997.000   0.021
## postfalse_2_sharing          0.205    0.139    0.271    6.116   2997.000   0.000
## postfalse_3_sharing         -0.139   -0.205   -0.073   -4.147   2997.000   0.000
## postfalse_4_sharing          0.507    0.441    0.573   15.126   2997.000   0.000
## --------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.876   
##   Residual                    0.749   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.577 
## -------------------------------</code></pre>
<pre class="r"><code>model_summary &lt;- summary(h1b_india)
coefs &lt;- fixef(h1b_india)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink postfalse_2_sharing 
##             0.00000          -105.04941          -111.61688           -86.01485 
## postfalse_3_sharing postfalse_4_sharing 
##          -109.48261           -65.41234</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1b_india)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink postfalse_2_sharing 
##           48.861364           -2.467209           -5.676165            6.833333 
## postfalse_3_sharing postfalse_4_sharing 
##           -4.633333           16.900000</code></pre>
</div>
<div id="plots-1" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>library(dplyr)
library(jtools)
library(ggplot2)

p &lt;- plot_summs(
                h1a_uk,
                h1a_brazil,
                h1a_india,
                h1a_all,
                
                h1b_uk,
                h1b_brazil,
                h1b_india,
                h1b_all,
                coefs = c(&quot;1&quot; = &quot;conditioncorrection&quot;,
                          &quot;2&quot; = &quot;conditionlink&quot;),
                legend.title = &quot;&quot;, colors = &quot;Rainbow&quot;,
                scale = T, robust = T) +
  theme(axis.text.y = element_text(face = &quot;bold&quot;, size = 11))</code></pre>
<pre><code>## Registered S3 methods overwritten by &#39;broom&#39;:
##   method            from  
##   tidy.glht         jtools
##   tidy.summary.glht jtools</code></pre>
<pre><code>## Loading required namespace: broom.mixed</code></pre>
<pre class="r"><code>p</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
<pre class="r"><code>df &lt;- p$data
df &lt;- df %&gt;%
  mutate(Country = rep(c(&quot;UK&quot;,&quot;UK&quot;, &quot;Brazil&quot;,&quot;Brazil&quot;,&quot;India&quot;,&quot;India&quot;,&quot;Combined&quot;,&quot;Combined&quot;,
                         &quot;UK&quot;,&quot;UK&quot;, &quot;Brazil&quot;,&quot;Brazil&quot;,&quot;India&quot;,&quot;India&quot;,&quot;Combined&quot;,&quot;Combined&quot;)))%&gt;%
  mutate(DV = rep(c(&quot;Accuracy&quot;,&quot;Accuracy&quot;,&quot;Accuracy&quot;,&quot;Accuracy&quot;,
                    &quot;Accuracy&quot;,&quot;Accuracy&quot;,&quot;Accuracy&quot;, &quot;Accuracy&quot;,
                    &quot;Sharing&quot;,&quot;Sharing&quot;,&quot;Sharing&quot;,&quot;Sharing&quot;,
                    &quot;Sharing&quot;,&quot;Sharing&quot;,&quot;Sharing&quot;,&quot;Sharing&quot;)))%&gt;%
  mutate(Condition = rep(c(&quot;Correction&quot;,&quot;Correction + Link&quot;,&quot;Correction&quot;, &quot;Correction + Link&quot;,
                           &quot;Correction&quot;,&quot;Correction + Link&quot;,&quot;Correction&quot;, &quot;Correction + Link&quot;,
                    &quot;Correction&quot;,&quot;Correction + Link&quot;,&quot;Correction&quot;, &quot;Correction + Link&quot;, 
                    &quot;Correction&quot;,&quot;Correction + Link&quot;,&quot;Correction&quot;, &quot;Correction + Link&quot;)))%&gt;%
  mutate(DV = factor(DV, levels = c(&quot;Sharing&quot;,&quot;Accuracy&quot;)))%&gt;%
  mutate(Country = factor(Country, levels = c(&quot;Combined&quot;,&quot;India&quot;,&quot;Brazil&quot;,&quot;UK&quot;)))%&gt;%
  mutate(Condition = factor(Condition, levels = c(&quot;Correction + Link&quot;,&quot;Correction&quot;)))

effi_effects_grouped &lt;- ggplot(data = df) +
  aes(x = estimate, y = Condition, xmin = conf.low, xmax = conf.high, color = Country, shape = DV) +
  geom_vline(xintercept = 0, lty = 1, lwd = 0.2) +
  geom_pointrange(position = position_dodge2(0.6)) +
  labs(x = &quot;PASSED&quot;, y = &quot;&quot;) +
  theme_light() +
  theme(strip.background = element_blank(), strip.text = element_text(color = &quot;black&quot;, size = 15, face = &quot;italic&quot;), axis.text.y = element_text(size = 12))+
  scale_shape_manual(
    values = c(&quot;Accuracy&quot; = 15, &quot;Sharing&quot; = 17),
    breaks = c(&quot;Accuracy&quot;, &quot;Sharing&quot;)) +
  scale_color_manual(
    values = c(&quot;UK&quot; = &quot;royalblue2&quot;, &quot;Brazil&quot; = &quot;#009C3B&quot;,&quot;India&quot; = &quot;#FF671F&quot;,&quot;Combined&quot; = &quot;#000000&quot;),
    breaks = c(&quot;UK&quot;, &quot;Brazil&quot;,&quot;India&quot;,&quot;Combined&quot;),
    labels = c(&quot;UK&quot;, &quot;Brazil&quot;,&quot;India&quot;,&quot;Combined&quot;),
    guide = guide_legend(override.aes = list(shape = 16,linetype = 0, size = 1.4, alpha = 0.5)))+
  scale_alpha_continuous(range = c(0.4, 1),guide = &quot;none&quot;) # Adjust transparency

effi_effects_grouped</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
<pre class="r"><code>ggsave(&quot;Fig_everything_results_CHECK_YES.pdf&quot;, effi_effects_grouped, width = 6, height = 4)</code></pre>
<pre class="r"><code>h1b_uk_results &lt;- ggpredict(h1b_uk, terms = c(&quot;condition&quot;))
h1b_brazil_results &lt;- ggpredict(h1b_brazil, terms = c(&quot;condition&quot;))
h1b_india_results &lt;- ggpredict(h1b_india, terms = c(&quot;condition&quot;))</code></pre>
<pre class="r"><code>h1b_uk_plot &lt;- ggplot(h1b_uk_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction&quot;,&quot;Correction\n + link&quot;)) +
    scale_y_continuous(limits = c(0,2), breaks = c(0,1,2), expand = c(0,0), labels=c(&quot;Not at all\n likely&quot;, &quot;Not very\n likely&quot;, &quot;Somewhat\n likely&quot;)) +
  ylab(&quot;Likelihood of sharing&quot;) +
  xlab(&quot;&quot;) +
  ggtitle(&quot;UK&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;,
        plot.title = element_text(hjust = 0.5),
        axis.text.x = element_text(size=11),
        axis.text.y = element_text(size=10),
        axis.title.y = element_text(size=15,face=&quot;bold&quot;),
        title = element_text(size=12,face=&quot;bold&quot;))

h1b_brazil_plot &lt;- ggplot(h1b_brazil_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction&quot;,&quot;Correction\n + link&quot;)) +
  scale_y_continuous(limits = c(0,2),breaks = c(0,1,2),expand = c(0,0)) +
  ylab(&quot;Accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Brazil&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.title.x=element_text(size=14,face=&quot;bold&quot;),
        axis.text.y=element_blank(),
        axis.text.x = element_text(size=11),
        legend.position = &quot;none&quot;,
        plot.title = element_text(hjust = 0.5),
        title = element_text(size=12,face=&quot;bold&quot;))

h1b_india_plot &lt;- ggplot(h1b_india_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction&quot;,&quot;Correction\n + link&quot;)) +
  scale_y_continuous(limits = c(0,2), breaks = c(0,1,2),expand = c(0,0)) +
  ylab(&quot;Accuracy&quot;) +
  xlab(&quot;&quot;) +
  ggtitle(&quot;India&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.text.x = element_text(size=11),
        axis.title.x=element_blank(),
        legend.position = &quot;none&quot;,
        plot.title = element_text(hjust = 0.5),
        title = element_text(size=12,face=&quot;bold&quot;))</code></pre>
</div>
</div>
<div id="h2a" class="section level2">
<h2>H2a</h2>
<div id="models-2" class="section level3">
<h3>Models</h3>
<p>We can formally test this simply by changing the reference category
in the models from H1a.</p>
<pre class="r"><code>h2a_all &lt;- lmer(accuracy ~ relevel(condition, ref = &quot;correction&quot;) + (1|post:country) +(1 | ResponseId), data=subset(corrections_accuracy_long))
summ(h2a_all, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 12000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 31582.315, BIC = 31626.671
## Pseudo-R² (fixed effects) = 0.002
## Pseudo-R² (total) = 0.512 
## 
## FIXED EFFECTS:
## ----------------------------------------------------------------------------------
##                                  Est.     2.5%   97.5%   t val.       d.f.       p
## ---------------------------- -------- -------- ------- -------- ---------- -------
## (Intercept)                     1.122    0.863   1.381    8.482     11.548   0.000
## relevel(condition, ref =        0.057   -0.009   0.122    1.702   2994.909   0.089
## &quot;correction&quot;)control                                                              
## relevel(condition, ref =       -0.054   -0.119   0.010   -1.650   2994.906   0.099
## &quot;correction&quot;)link                                                                 
## ----------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.634   
##  post:country   (Intercept)     0.451   
##    Residual                     0.761   
## ----------------------------------------
## 
## Grouping variables:
## ---------------------------------
##     Group       # groups    ICC  
## -------------- ---------- -------
##   ResponseId      3000     0.339 
##  post:country      12      0.172 
## ---------------------------------</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h2a_all)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##                                   (Intercept) 
##                                       0.00000 
## relevel(condition, ref = &quot;correction&quot;)control 
##                                     -94.96384 
##    relevel(condition, ref = &quot;correction&quot;)link 
##                                    -104.85546</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h2a_all)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##                                   (Intercept) 
##                                     37.396503 
## relevel(condition, ref = &quot;correction&quot;)control 
##                                      1.883349 
##    relevel(condition, ref = &quot;correction&quot;)link 
##                                     -1.815773</code></pre>
<pre class="r"><code>h2a_uk &lt;- lmer(accuracy ~ relevel(condition, ref = &quot;correction&quot;) + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;UK&quot;))
summ(h2a_uk, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9393.685, BIC = 9444.038
## Pseudo-R² (fixed effects) = 0.046
## Pseudo-R² (total) = 0.462 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------------------
##                                  Est.     2.5%    97.5%    t val.       d.f.       p
## ---------------------------- -------- -------- -------- --------- ---------- -------
## (Intercept)                     0.855    0.775    0.936    20.868   1493.936   0.000
## relevel(condition, ref =        0.010   -0.091    0.111     0.198    997.000   0.843
## &quot;correction&quot;)control                                                                
## relevel(condition, ref =       -0.060   -0.161    0.040    -1.176    997.000   0.240
## &quot;correction&quot;)link                                                                   
## postfalse_2_accuracy           -0.304   -0.361   -0.247   -10.408   2997.000   0.000
## postfalse_3_accuracy           -0.078   -0.135   -0.021    -2.670   2997.000   0.008
## postfalse_4_accuracy            0.226    0.169    0.283     7.737   2997.000   0.000
## ------------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.574   
##   Residual                    0.653   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.436 
## -------------------------------</code></pre>
<pre class="r"><code>h2a_brazil &lt;- lmer(accuracy ~ relevel(condition, ref = &quot;correction&quot;) + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;Brazil&quot;))
summ(h2a_brazil, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10893.943, BIC = 10944.295
## Pseudo-R² (fixed effects) = 0.078
## Pseudo-R² (total) = 0.330 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------------------
##                                  Est.     2.5%    97.5%    t val.       d.f.       p
## ---------------------------- -------- -------- -------- --------- ---------- -------
## (Intercept)                     1.363    1.279    1.447    31.797   1859.020   0.000
## relevel(condition, ref =        0.083   -0.018    0.184     1.606    997.000   0.109
## &quot;correction&quot;)control                                                                
## relevel(condition, ref =       -0.017   -0.117    0.083    -0.327    997.000   0.744
## &quot;correction&quot;)link                                                                   
## postfalse_2_accuracy           -0.501   -0.574   -0.428   -13.373   2997.000   0.000
## postfalse_3_accuracy           -0.783   -0.856   -0.710   -20.901   2997.000   0.000
## postfalse_4_accuracy           -0.363   -0.436   -0.290    -9.690   2997.000   0.000
## ------------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.515   
##   Residual                    0.838   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.274 
## -------------------------------</code></pre>
<pre class="r"><code>h2a_india &lt;- lmer(accuracy ~ relevel(condition, ref = &quot;correction&quot;) + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;India&quot;))
summ(h2a_india, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 11027.932, BIC = 11078.285
## Pseudo-R² (fixed effects) = 0.078
## Pseudo-R² (total) = 0.540 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------------------
##                                  Est.     2.5%    97.5%   t val.       d.f.       p
## ---------------------------- -------- -------- -------- -------- ---------- -------
## (Intercept)                     1.442    1.339    1.545   27.545   1418.227   0.000
## relevel(condition, ref =        0.077   -0.056    0.209    1.128    997.000   0.260
## &quot;correction&quot;)control                                                               
## relevel(condition, ref =       -0.087   -0.220    0.045   -1.292    997.000   0.197
## &quot;correction&quot;)link                                                                  
## postfalse_2_accuracy            0.227    0.159    0.295    6.495   2997.000   0.000
## postfalse_3_accuracy           -0.226   -0.294   -0.158   -6.467   2997.000   0.000
## postfalse_4_accuracy            0.628    0.560    0.696   17.970   2997.000   0.000
## -----------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.782   
##   Residual                    0.781   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.501 
## -------------------------------</code></pre>
</div>
</div>
<div id="h2b" class="section level2">
<h2>H2b</h2>
<div id="models-3" class="section level3">
<h3>Models</h3>
<p>We can formally test this simply by changing the reference category
in the models from H1b.</p>
<pre class="r"><code>h2b_all &lt;- lmer(sharing ~ relevel(condition, ref = &quot;correction&quot;) + +(1|post:country)+ (1 | ResponseId), data=subset(corrections_sharing_long))
summ(h2b_all, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 12000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 29002.641, BIC = 29046.997
## Pseudo-R² (fixed effects) = 0.001
## Pseudo-R² (total) = 0.671 
## 
## FIXED EFFECTS:
## ----------------------------------------------------------------------------------
##                                  Est.     2.5%   97.5%   t val.       d.f.       p
## ---------------------------- -------- -------- ------- -------- ---------- -------
## (Intercept)                     0.861    0.564   1.157    5.694     11.466   0.000
## relevel(condition, ref =        0.066   -0.006   0.138    1.796   2994.866   0.073
## &quot;correction&quot;)control                                                              
## relevel(condition, ref =       -0.028   -0.099   0.044   -0.758   2994.862   0.449
## &quot;correction&quot;)link                                                                 
## ----------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.751   
##  post:country   (Intercept)     0.516   
##    Residual                     0.638   
## ----------------------------------------
## 
## Grouping variables:
## ---------------------------------
##     Group       # groups    ICC  
## -------------- ---------- -------
##   ResponseId      3000     0.456 
##  post:country      12      0.215 
## ---------------------------------</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h2b_all)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##                                   (Intercept) 
##                                       0.00000 
## relevel(condition, ref = &quot;correction&quot;)control 
##                                     -92.35665 
##    relevel(condition, ref = &quot;correction&quot;)link 
##                                    -103.20690</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h2b_all)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##                                   (Intercept) 
##                                    28.6909857 
## relevel(condition, ref = &quot;correction&quot;)control 
##                                     2.1929520 
##    relevel(condition, ref = &quot;correction&quot;)link 
##                                    -0.9200903</code></pre>
<pre class="r"><code>h2b_uk &lt;- lmer(sharing ~ relevel(condition, ref = &quot;correction&quot;) + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;UK&quot;))
summ(h2b_uk, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 7146.206, BIC = 7196.559
## Pseudo-R² (fixed effects) = 0.002
## Pseudo-R² (total) = 0.712 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------------------
##                                  Est.     2.5%    97.5%   t val.       d.f.       p
## ---------------------------- -------- -------- -------- -------- ---------- -------
## (Intercept)                     0.483    0.401    0.565   11.530   1178.208   0.000
## relevel(condition, ref =        0.009   -0.101    0.119    0.155    996.999   0.877
## &quot;correction&quot;)control                                                               
## relevel(condition, ref =       -0.032   -0.142    0.077   -0.580    996.999   0.562
## &quot;correction&quot;)link                                                                  
## postfalse_2_sharing            -0.083   -0.121   -0.045   -4.254   2997.000   0.000
## postfalse_3_sharing            -0.006   -0.044    0.032   -0.307   2997.000   0.758
## postfalse_4_sharing            -0.015   -0.053    0.023   -0.769   2997.000   0.442
## -----------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.686   
##   Residual                    0.436   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.712 
## -------------------------------</code></pre>
<pre class="r"><code>h2b_brazil &lt;- lmer(sharing ~ relevel(condition, ref = &quot;correction&quot;) + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;Brazil&quot;))
summ(h2b_brazil, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9951.107, BIC = 10001.460
## Pseudo-R² (fixed effects) = 0.026
## Pseudo-R² (total) = 0.504 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------------------
##                                  Est.     2.5%    97.5%    t val.       d.f.       p
## ---------------------------- -------- -------- -------- --------- ---------- -------
## (Intercept)                     0.830    0.741    0.918    18.322   1433.597   0.000
## relevel(condition, ref =        0.115   -0.000    0.230     1.955    997.000   0.051
## &quot;correction&quot;)control                                                                
## relevel(condition, ref =        0.045   -0.069    0.159     0.766    997.000   0.444
## &quot;correction&quot;)link                                                                   
## postfalse_2_sharing            -0.316   -0.376   -0.256   -10.306   2997.000   0.000
## postfalse_3_sharing            -0.397   -0.457   -0.337   -12.948   2997.000   0.000
## postfalse_4_sharing            -0.242   -0.302   -0.182    -7.893   2997.000   0.000
## ------------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.673   
##   Residual                    0.686   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.491 
## -------------------------------</code></pre>
<pre class="r"><code>h2b_india &lt;- lmer(sharing ~ relevel(condition, ref = &quot;correction&quot;) + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;India&quot;))
summ(h2b_india, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10948.938, BIC = 10999.291
## Pseudo-R² (fixed effects) = 0.046
## Pseudo-R² (total) = 0.597 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------------------
##                                  Est.     2.5%    97.5%   t val.       d.f.       p
## ---------------------------- -------- -------- -------- -------- ---------- -------
## (Intercept)                     1.392    1.282    1.502   24.869   1320.327   0.000
## relevel(condition, ref =        0.074   -0.071    0.219    1.001    997.000   0.317
## &quot;correction&quot;)control                                                               
## relevel(condition, ref =       -0.096   -0.241    0.048   -1.307    997.000   0.191
## &quot;correction&quot;)link                                                                  
## postfalse_2_sharing             0.205    0.139    0.271    6.116   2997.000   0.000
## postfalse_3_sharing            -0.139   -0.205   -0.073   -4.147   2997.000   0.000
## postfalse_4_sharing             0.507    0.441    0.573   15.126   2997.000   0.000
## -----------------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.876   
##   Residual                    0.749   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.577 
## -------------------------------</code></pre>
</div>
</div>
<div id="rq2a" class="section level2">
<h2>RQ2a</h2>
<div id="models-4" class="section level3">
<h3>Models</h3>
<pre class="r"><code>rq2a_all &lt;- lmer(accuracy ~ condition*consp_mean + +(1|post:country)+ (1 | ResponseId), data=corrections_accuracy_long)
summ(rq2a_all)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 12000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 31311.32, BIC = 31377.85
## Pseudo-R² (fixed effects) = 0.05
## Pseudo-R² (total) = 0.50 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------------
##                                         Est.   S.E.   t val.      d.f.      p
## ------------------------------------ ------- ------ -------- --------- ------
## (Intercept)                             1.20   0.12    10.08     11.63   0.00
## conditioncorrection                    -0.07   0.03    -2.25   2991.91   0.02
## conditionlink                          -0.11   0.03    -3.61   2991.90   0.00
## consp_mean                              0.26   0.02    11.20   2993.18   0.00
## conditioncorrection:consp_mean         -0.02   0.03    -0.49   2991.95   0.63
## conditionlink:consp_mean               -0.05   0.03    -1.60   2991.90   0.11
## -----------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.59    
##  post:country   (Intercept)     0.41    
##    Residual                     0.76    
## ----------------------------------------
## 
## Grouping variables:
## --------------------------------
##     Group       # groups   ICC  
## -------------- ---------- ------
##   ResponseId      3000     0.32 
##  post:country      12      0.15 
## --------------------------------</code></pre>
<pre class="r"><code>confint(rq2a_all)</code></pre>
<pre><code>## Computing profile confidence intervals ...</code></pre>
<pre><code>##                                      2.5 %       97.5 %
## .sig01                          0.57106093  0.614045901
## .sig02                          0.27219971  0.619202964
## .sigma                          0.75035964  0.772618422
## (Intercept)                     0.96195445  1.447697450
## conditioncorrection            -0.13369040 -0.009346477
## conditionlink                  -0.17631004 -0.052354497
## consp_mean                      0.21486641  0.305911014
## conditioncorrection:consp_mean -0.07983874  0.048043954
## conditionlink:consp_mean       -0.11384584  0.011586312</code></pre>
<pre class="r"><code>rq2a_uk &lt;- lmer(accuracy ~ condition*consp_mean + post + (1 | ResponseId) , data=subset(corrections_accuracy_long, country==&quot;UK&quot;))
summ(rq2a_uk)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9187.44, BIC = 9256.68
## Pseudo-R² (fixed effects) = 0.16
## Pseudo-R² (total) = 0.46 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------------
##                                         Est.   S.E.   t val.      d.f.      p
## ------------------------------------ ------- ------ -------- --------- ------
## (Intercept)                             0.95   0.04    25.19   1608.27   0.00
## conditioncorrection                    -0.03   0.05    -0.58    994.00   0.56
## conditionlink                          -0.09   0.05    -1.84    994.00   0.07
## consp_mean                              0.30   0.03    10.14    994.00   0.00
## postfalse_2_accuracy                   -0.30   0.03   -10.41   2997.00   0.00
## postfalse_3_accuracy                   -0.08   0.03    -2.67   2997.00   0.01
## postfalse_4_accuracy                    0.23   0.03     7.74   2997.00   0.00
## conditioncorrection:consp_mean         -0.01   0.04    -0.29    994.00   0.77
## conditionlink:consp_mean               -0.07   0.04    -1.70    994.00   0.09
## -----------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.49    
##   Residual                    0.65    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.36 
## ------------------------------</code></pre>
<pre class="r"><code>confint(rq2a_uk)</code></pre>
<pre><code>## Computing profile confidence intervals ...</code></pre>
<pre><code>##                                      2.5 %       97.5 %
## .sig01                          0.45881476  0.521858361
## .sigma                          0.63664018  0.669689567
## (Intercept)                     0.87716558  1.024859421
## conditioncorrection            -0.12010325  0.065250864
## conditionlink                  -0.17768894  0.005656883
## consp_mean                      0.24573143  0.363201807
## postfalse_2_accuracy           -0.36123916 -0.246760844
## postfalse_3_accuracy           -0.13523916 -0.020760844
## postfalse_4_accuracy            0.16876084  0.283239156
## conditioncorrection:consp_mean -0.09804266  0.072556701
## conditionlink:consp_mean       -0.15145236  0.010632141</code></pre>
<pre class="r"><code>rq2a_brazil &lt;- lmer(accuracy ~ condition*consp_mean + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;Brazil&quot;))
summ(rq2a_brazil)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10854.60, BIC = 10923.83
## Pseudo-R² (fixed effects) = 0.10
## Pseudo-R² (total) = 0.33 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------------
##                                         Est.   S.E.   t val.      d.f.      p
## ------------------------------------ ------- ------ -------- --------- ------
## (Intercept)                             1.49   0.04    34.12   1814.35   0.00
## conditioncorrection                    -0.09   0.05    -1.67    994.00   0.10
## conditionlink                          -0.08   0.05    -1.62    994.00   0.11
## consp_mean                              0.18   0.04     4.19    994.00   0.00
## postfalse_2_accuracy                   -0.50   0.04   -13.37   2997.00   0.00
## postfalse_3_accuracy                   -0.78   0.04   -20.90   2997.00   0.00
## postfalse_4_accuracy                   -0.36   0.04    -9.69   2997.00   0.00
## conditioncorrection:consp_mean         -0.02   0.06    -0.39    994.00   0.69
## conditionlink:consp_mean                0.05   0.06     0.83    994.00   0.41
## -----------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.49    
##   Residual                    0.84    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.26 
## ------------------------------</code></pre>
<pre class="r"><code>confint(rq2a_brazil)</code></pre>
<pre><code>## Computing profile confidence intervals ...</code></pre>
<pre><code>##                                      2.5 %      97.5 %
## .sig01                          0.45063200  0.52722179
## .sigma                          0.81651924  0.85890654
## (Intercept)                     1.40113585  1.57161595
## conditioncorrection            -0.18889793  0.01510638
## conditionlink                  -0.18609196  0.01746001
## consp_mean                      0.09516563  0.26143754
## postfalse_2_accuracy           -0.57441175 -0.42758825
## postfalse_3_accuracy           -0.85641175 -0.70958825
## postfalse_4_accuracy           -0.43641175 -0.28958825
## conditioncorrection:consp_mean -0.14324673  0.09511264
## conditionlink:consp_mean       -0.06695543  0.16483742</code></pre>
<pre class="r"><code>rq2a_india &lt;- lmer(accuracy ~ condition*consp_mean + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;India&quot;))
summ(rq2a_india)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10987.67, BIC = 11056.90
## Pseudo-R² (fixed effects) = 0.11
## Pseudo-R² (total) = 0.54 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------------
##                                         Est.   S.E.   t val.      d.f.      p
## ------------------------------------ ------- ------ -------- --------- ------
## (Intercept)                             1.47   0.05    27.91   1409.89   0.00
## conditioncorrection                    -0.11   0.07    -1.61    994.00   0.11
## conditionlink                          -0.15   0.07    -2.17    994.00   0.03
## consp_mean                              0.25   0.05     4.84    994.00   0.00
## postfalse_2_accuracy                    0.23   0.03     6.50   2997.00   0.00
## postfalse_3_accuracy                   -0.23   0.03    -6.47   2997.00   0.00
## postfalse_4_accuracy                    0.63   0.03    17.97   2997.00   0.00
## conditioncorrection:consp_mean          0.01   0.07     0.11    994.00   0.91
## conditionlink:consp_mean               -0.09   0.07    -1.21    994.00   0.23
## -----------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.76    
##   Residual                    0.78    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.48 
## ------------------------------</code></pre>
<pre class="r"><code>confint(rq2a_india)</code></pre>
<pre><code>## Computing profile confidence intervals ...</code></pre>
<pre><code>##                                     2.5 %      97.5 %
## .sig01                          0.7115536  0.79600557
## .sigma                          0.7617074  0.80124932
## (Intercept)                     1.3642308  1.56986547
## conditioncorrection            -0.2454272  0.02386076
## conditionlink                  -0.2795591 -0.01472559
## consp_mean                      0.1488253  0.35063382
## postfalse_2_accuracy            0.1585163  0.29548372
## postfalse_3_accuracy           -0.2944837 -0.15751628
## postfalse_4_accuracy            0.5595163  0.69648372
## conditioncorrection:consp_mean -0.1324605  0.14820309
## conditionlink:consp_mean       -0.2297132  0.05394302</code></pre>
</div>
<div id="plots-2" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>rq2a_uk_results &lt;- ggpredict(rq2a_uk, terms = c(&quot;condition&quot;, &quot;consp_mean&quot;))
rq2a_brazil_results &lt;- ggpredict(rq2a_brazil, terms = c(&quot;condition&quot;, &quot;consp_mean&quot;))
rq2a_india_results &lt;- ggpredict(rq2a_india, terms = c(&quot;condition&quot;, &quot;consp_mean&quot;))</code></pre>
<pre class="r"><code>rq2a_uk_plot &lt;- ggplot(rq2a_uk_results, aes(x, predicted, group=group)) +
   # geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
    ylab(&quot;accuracy&quot;) +
   #xlab(&quot;Condition&quot;) +
    ggtitle(&quot;UK&quot;) +
    scale_color_manual(&quot;Conspiracy\nideation&quot;, values=c(&quot;#99a9db&quot;, &quot;#60719f&quot;, &quot;#0D2042&quot;), labels=c(&quot;Low&quot;, &quot;Medium&quot;, &quot;High&quot;)) +
    theme_classic() +
    theme(axis.title.x=element_blank())

rq2a_brazil_plot &lt;- ggplot(rq2a_brazil_results, aes(x, predicted, group=group)) +
    #geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    #ylab(&quot;sharing&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;Brazil&quot;) +
    scale_color_manual(&quot;Conspiracy\nideation&quot;, values=c(&quot;#99a9db&quot;, &quot;#60719f&quot;, &quot;#0D2042&quot;), labels=c(&quot;Low&quot;, &quot;Medium&quot;, &quot;High&quot;)) +
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank())

rq2a_india_plot &lt;- ggplot(rq2a_india_results, aes(x, predicted, group=group)) +
    #geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    ylab(&quot;accuracy&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;India&quot;) +
    scale_color_manual(&quot;Conspiracy\nideation&quot;, values=c(&quot;#99a9db&quot;, &quot;#60719f&quot;, &quot;#0D2042&quot;), labels=c(&quot;Low&quot;, &quot;Medium&quot;, &quot;High&quot;)) +
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank(),
          axis.title.x=element_blank())

library(&quot;patchwork&quot;)
library(&quot;ggplot2&quot;)
final_plot &lt;- rq2a_uk_plot + rq2a_brazil_plot + rq2a_india_plot + plot_layout(guides = &#39;collect&#39;)
print(final_plot)</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
<pre class="r"><code>ggsave(&quot;Conspi.pdf&quot;, final_plot, width = 7, height = 5)</code></pre>
</div>
</div>
<div id="rq2b" class="section level2">
<h2>RQ2b</h2>
<div id="models-5" class="section level3">
<h3>Models</h3>
<pre class="r"><code>rq2b_all &lt;- lmer(sharing ~ condition*consp_mean + +(1|post:country)+(1 | ResponseId) , data=subset(corrections_sharing_long))
summ(rq2b_all, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 12000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 28811.281, BIC = 28877.815
## Pseudo-R² (fixed effects) = 0.042
## Pseudo-R² (total) = 0.658 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%   t val.
## ------------------------------------ -------- -------- -------- --------
## (Intercept)                             0.951    0.684    1.218    6.986
## conditioncorrection                    -0.079   -0.149   -0.010   -2.232
## conditionlink                          -0.096   -0.166   -0.027   -2.727
## consp_mean                              0.242    0.191    0.293    9.314
## conditioncorrection:consp_mean         -0.003   -0.074    0.069   -0.074
## conditionlink:consp_mean               -0.047   -0.117    0.023   -1.319
## ------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                              11.537   0.000
## conditioncorrection                    2991.823   0.026
## conditionlink                          2991.814   0.006
## consp_mean                             2993.061   0.000
## conditioncorrection:consp_mean         2991.863   0.941
## conditionlink:consp_mean               2991.813   0.187
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.720   
##  post:country   (Intercept)     0.464   
##    Residual                     0.638   
## ----------------------------------------
## 
## Grouping variables:
## ---------------------------------
##     Group       # groups    ICC  
## -------------- ---------- -------
##   ResponseId      3000     0.455 
##  post:country      12      0.188 
## ---------------------------------</code></pre>
<pre class="r"><code>rq2b_uk &lt;- lmer(sharing ~ condition*consp_mean + post + (1 | ResponseId) , data=subset(corrections_sharing_long, country==&quot;UK&quot;))
summ(rq2b_uk, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 7031.251, BIC = 7100.486
## Pseudo-R² (fixed effects) = 0.101
## Pseudo-R² (total) = 0.713 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%   t val.
## ------------------------------------ -------- -------- -------- --------
## (Intercept)                             0.559    0.481    0.637   14.053
## conditioncorrection                    -0.015   -0.121    0.091   -0.270
## conditionlink                          -0.043   -0.148    0.062   -0.800
## consp_mean                              0.238    0.171    0.305    6.944
## postfalse_2_sharing                    -0.083   -0.121   -0.045   -4.254
## postfalse_3_sharing                    -0.006   -0.044    0.032   -0.307
## postfalse_4_sharing                    -0.015   -0.053    0.023   -0.769
## conditioncorrection:consp_mean          0.022   -0.075    0.120    0.446
## conditionlink:consp_mean               -0.020   -0.113    0.073   -0.424
## ------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                            1197.272   0.000
## conditioncorrection                     994.000   0.787
## conditionlink                           994.000   0.424
## consp_mean                              994.000   0.000
## postfalse_2_sharing                    2997.000   0.000
## postfalse_3_sharing                    2997.000   0.758
## postfalse_4_sharing                    2997.000   0.442
## conditioncorrection:consp_mean          994.000   0.655
## conditionlink:consp_mean                994.000   0.671
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.637   
##   Residual                    0.436   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.681 
## -------------------------------</code></pre>
<pre class="r"><code>rq2b_brazil &lt;- lmer(sharing ~ condition*consp_mean + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;Brazil&quot;))
summ(rq2b_brazil, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9938.085, BIC = 10007.319
## Pseudo-R² (fixed effects) = 0.044
## Pseudo-R² (total) = 0.505 
## 
## FIXED EFFECTS:
## -------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%    t val.
## ------------------------------------ -------- -------- -------- ---------
## (Intercept)                             0.985    0.894    1.077    21.110
## conditioncorrection                    -0.125   -0.243   -0.007    -2.083
## conditionlink                          -0.070   -0.188    0.048    -1.168
## consp_mean                              0.179    0.083    0.275     3.655
## postfalse_2_sharing                    -0.316   -0.376   -0.256   -10.306
## postfalse_3_sharing                    -0.397   -0.457   -0.337   -12.948
## postfalse_4_sharing                    -0.242   -0.302   -0.182    -7.893
## conditioncorrection:consp_mean         -0.051   -0.189    0.086    -0.732
## conditionlink:consp_mean               -0.013   -0.147    0.121    -0.186
## -------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                            1397.507   0.000
## conditioncorrection                     994.000   0.038
## conditionlink                           994.000   0.243
## consp_mean                              994.000   0.000
## postfalse_2_sharing                    2997.000   0.000
## postfalse_3_sharing                    2997.000   0.000
## postfalse_4_sharing                    2997.000   0.000
## conditioncorrection:consp_mean          994.000   0.464
## conditionlink:consp_mean                994.000   0.853
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.661   
##   Residual                    0.686   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.482 
## -------------------------------</code></pre>
<pre class="r"><code>rq2b_india &lt;- lmer(sharing ~ condition*consp_mean + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;India&quot;))
summ(rq2b_india, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10902.179, BIC = 10971.413
## Pseudo-R² (fixed effects) = 0.087
## Pseudo-R² (total) = 0.598 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%   t val.
## ------------------------------------ -------- -------- -------- --------
## (Intercept)                             1.408    1.298    1.518   25.126
## conditioncorrection                    -0.113   -0.260    0.034   -1.511
## conditionlink                          -0.156   -0.300   -0.012   -2.120
## consp_mean                              0.279    0.169    0.389    4.979
## postfalse_2_sharing                     0.205    0.139    0.271    6.116
## postfalse_3_sharing                    -0.139   -0.205   -0.073   -4.147
## postfalse_4_sharing                     0.507    0.441    0.573   15.126
## conditioncorrection:consp_mean          0.011   -0.142    0.164    0.139
## conditionlink:consp_mean               -0.078   -0.233    0.076   -0.994
## ------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                            1315.220   0.000
## conditioncorrection                     994.000   0.131
## conditionlink                           994.000   0.034
## consp_mean                              994.000   0.000
## postfalse_2_sharing                    2997.000   0.000
## postfalse_3_sharing                    2997.000   0.000
## postfalse_4_sharing                    2997.000   0.000
## conditioncorrection:consp_mean          994.000   0.889
## conditionlink:consp_mean                994.000   0.320
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.845   
##   Residual                    0.749   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.559 
## -------------------------------</code></pre>
</div>
<div id="plots-3" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>rq2b_uk_results &lt;- ggpredict(rq2b_uk, terms = c(&quot;condition&quot;, &quot;consp_mean&quot;))
rq2b_brazil_results &lt;- ggpredict(rq2b_brazil, terms = c(&quot;condition&quot;, &quot;consp_mean&quot;))
rq2b_india_results &lt;- ggpredict(rq2b_india, terms = c(&quot;condition&quot;, &quot;consp_mean&quot;))</code></pre>
<pre class="r"><code>rq2b_uk_plot &lt;- ggplot(rq2b_uk_results, aes(x, predicted, group=group)) +
   # geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n likely&quot;, &quot;Not very\n likely&quot;, &quot;Somewhat\n likely&quot;, &quot;Very\n likely&quot;)) +
    ylab(&quot;Sharing&quot;) +
   #xlab(&quot;Condition&quot;) +
    ggtitle(&quot;UK&quot;) +
    scale_color_manual(&quot;Conspiracy\nideation&quot;, values=c(&quot;#99a9db&quot;, &quot;#60719f&quot;, &quot;#0D2042&quot;), labels=c(&quot;Low&quot;, &quot;Medium&quot;, &quot;High&quot;)) +
    theme_classic() +
    theme(axis.title.x=element_blank())

rq2b_brazil_plot &lt;- ggplot(rq2b_brazil_results, aes(x, predicted, group=group)) +
   # geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    #ylab(&quot;sharing&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;Brazil&quot;) +
    scale_color_manual(&quot;Conspiracy\nideation&quot;, values=c(&quot;#99a9db&quot;, &quot;#60719f&quot;, &quot;#0D2042&quot;), labels=c(&quot;Low&quot;, &quot;Medium&quot;, &quot;High&quot;)) +
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank())

rq2b_india_plot &lt;- ggplot(rq2b_india_results, aes(x, predicted, group=group)) +
   # geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    ylab(&quot;sharing&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;India&quot;) +
    scale_color_manual(&quot;Conspiracy\nideation&quot;, values=c(&quot;#99a9db&quot;, &quot;#60719f&quot;, &quot;#0D2042&quot;), labels=c(&quot;Low&quot;, &quot;Medium&quot;, &quot;High&quot;)) +
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank(),
          axis.title.x=element_blank())

final_plot &lt;-rq2b_uk_plot + rq2b_brazil_plot + rq2b_india_plot + plot_layout(guides = &#39;collect&#39;)
print(final_plot)</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
<pre class="r"><code>ggsave(&quot;ConspiSha.pdf&quot;, final_plot, width = 7, height = 5)</code></pre>
</div>
</div>
<div id="rq3a" class="section level2">
<h2>RQ3a</h2>
<div id="models-6" class="section level3">
<h3>Models</h3>
<pre class="r"><code># Is the effect of correction moderated by trust in Social Media?
rq3a_all &lt;- lmer(accuracy ~ condition*Trust_SM +(1|post:country)+ (1 | ResponseId) , data=subset(corrections_accuracy_long))
summ(rq3a_all, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 12000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 31262.442, BIC = 31328.976
## Pseudo-R² (fixed effects) = 0.070
## Pseudo-R² (total) = 0.486 
## 
## FIXED EFFECTS:
## ----------------------------------------------------------------------
##                                        Est.     2.5%    97.5%   t val.
## ---------------------------------- -------- -------- -------- --------
## (Intercept)                           0.829    0.615    1.043    7.600
## conditioncorrection                  -0.082   -0.183    0.019   -1.588
## conditionlink                        -0.114   -0.213   -0.015   -2.251
## Trust_SM                              0.225    0.188    0.262   11.844
## conditioncorrection:Trust_SM          0.002   -0.048    0.052    0.082
## conditionlink:Trust_SM               -0.002   -0.052    0.048   -0.078
## ----------------------------------------------------------------------
##  
## -----------------------------------------------------
##                                          d.f.       p
## ---------------------------------- ---------- -------
## (Intercept)                            13.724   0.000
## conditioncorrection                  2991.954   0.112
## conditionlink                        2991.917   0.024
## Trust_SM                             2999.471   0.000
## conditioncorrection:Trust_SM         2991.933   0.935
## conditionlink:Trust_SM               2991.927   0.938
## -----------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.586   
##  post:country   (Intercept)     0.356   
##    Residual                     0.761   
## ----------------------------------------
## 
## Grouping variables:
## ---------------------------------
##     Group       # groups    ICC  
## -------------- ---------- -------
##   ResponseId      3000     0.327 
##  post:country      12      0.121 
## ---------------------------------</code></pre>
<pre class="r"><code>rq3a_uk &lt;- lmer(accuracy ~ condition*Trust_SM + post + (1 | ResponseId) , data=subset(corrections_accuracy_long, country==&quot;UK&quot;))
summ(rq3a_uk, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9210.816, BIC = 9280.050
## Pseudo-R² (fixed effects) = 0.148
## Pseudo-R² (total) = 0.463 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------
##                                        Est.     2.5%    97.5%    t val.
## ---------------------------------- -------- -------- -------- ---------
## (Intercept)                           0.614    0.521    0.707    12.969
## conditioncorrection                  -0.022   -0.145    0.102    -0.344
## conditionlink                        -0.058   -0.177    0.061    -0.956
## Trust_SM                              0.269    0.207    0.330     8.548
## postfalse_2_accuracy                 -0.304   -0.361   -0.247   -10.408
## postfalse_3_accuracy                 -0.078   -0.135   -0.021    -2.670
## postfalse_4_accuracy                  0.226    0.169    0.283     7.737
## conditioncorrection:Trust_SM         -0.003   -0.089    0.083    -0.064
## conditionlink:Trust_SM               -0.004   -0.089    0.081    -0.103
## -----------------------------------------------------------------------
##  
## -----------------------------------------------------
##                                          d.f.       p
## ---------------------------------- ---------- -------
## (Intercept)                          1340.066   0.000
## conditioncorrection                   994.000   0.731
## conditionlink                         994.000   0.339
## Trust_SM                              994.000   0.000
## postfalse_2_accuracy                 2997.000   0.000
## postfalse_3_accuracy                 2997.000   0.008
## postfalse_4_accuracy                 2997.000   0.000
## conditioncorrection:Trust_SM          994.000   0.949
## conditionlink:Trust_SM                994.000   0.918
## -----------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.500   
##   Residual                    0.653   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.369 
## -------------------------------</code></pre>
<pre class="r"><code>rq3a_brazil &lt;- lmer(accuracy ~ condition*Trust_SM + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;Brazil&quot;))
summ(rq3a_brazil, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10908.867, BIC = 10978.101
## Pseudo-R² (fixed effects) = 0.080
## Pseudo-R² (total) = 0.331 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------
##                                        Est.     2.5%    97.5%    t val.
## ---------------------------------- -------- -------- -------- ---------
## (Intercept)                           1.413    1.278    1.549    20.438
## conditioncorrection                  -0.106   -0.288    0.075    -1.147
## conditionlink                        -0.179   -0.361    0.004    -1.913
## Trust_SM                              0.023   -0.051    0.096     0.599
## postfalse_2_accuracy                 -0.501   -0.574   -0.428   -13.373
## postfalse_3_accuracy                 -0.783   -0.856   -0.710   -20.901
## postfalse_4_accuracy                 -0.363   -0.436   -0.290    -9.690
## conditioncorrection:Trust_SM          0.015   -0.089    0.118     0.283
## conditionlink:Trust_SM                0.051   -0.053    0.154     0.960
## -----------------------------------------------------------------------
##  
## -----------------------------------------------------
##                                          d.f.       p
## ---------------------------------- ---------- -------
## (Intercept)                          1248.782   0.000
## conditioncorrection                   994.000   0.252
## conditionlink                         994.000   0.056
## Trust_SM                              994.000   0.549
## postfalse_2_accuracy                 2997.000   0.000
## postfalse_3_accuracy                 2997.000   0.000
## postfalse_4_accuracy                 2997.000   0.000
## conditioncorrection:Trust_SM          994.000   0.777
## conditionlink:Trust_SM                994.000   0.337
## -----------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.514   
##   Residual                    0.838   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.273 
## -------------------------------</code></pre>
<pre class="r"><code>rq3a_india &lt;- lmer(accuracy ~ condition*Trust_SM + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;India&quot;))
summ(rq3a_india, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10851.706, BIC = 10920.941
## Pseudo-R² (fixed effects) = 0.181
## Pseudo-R² (total) = 0.540 
## 
## FIXED EFFECTS:
## ----------------------------------------------------------------------
##                                        Est.     2.5%    97.5%   t val.
## ---------------------------------- -------- -------- -------- --------
## (Intercept)                           0.864    0.677    1.050    9.081
## conditioncorrection                  -0.257   -0.525    0.012   -1.870
## conditionlink                        -0.217   -0.478    0.044   -1.628
## Trust_SM                              0.286    0.216    0.356    8.014
## postfalse_2_accuracy                  0.227    0.159    0.295    6.495
## postfalse_3_accuracy                 -0.226   -0.294   -0.158   -6.467
## postfalse_4_accuracy                  0.628    0.560    0.696   17.970
## conditioncorrection:Trust_SM          0.051   -0.050    0.152    0.996
## conditionlink:Trust_SM                0.020   -0.081    0.120    0.384
## ----------------------------------------------------------------------
##  
## -----------------------------------------------------
##                                          d.f.       p
## ---------------------------------- ---------- -------
## (Intercept)                          1101.837   0.000
## conditioncorrection                   994.000   0.062
## conditionlink                         994.000   0.104
## Trust_SM                              994.000   0.000
## postfalse_2_accuracy                 2997.000   0.000
## postfalse_3_accuracy                 2997.000   0.000
## postfalse_4_accuracy                 2997.000   0.000
## conditioncorrection:Trust_SM          994.000   0.320
## conditionlink:Trust_SM                994.000   0.701
## -----------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.691   
##   Residual                    0.781   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.439 
## -------------------------------</code></pre>
</div>
<div id="plots-4" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>rq3a_uk_results &lt;- ggpredict(rq3a_uk, terms = c(&quot;condition&quot;, &quot;Trust_SM&quot;))
rq3a_india_results &lt;- ggpredict(rq3a_india, terms = c(&quot;condition&quot;, &quot;Trust_SM&quot;))
rq3a_brazil_results &lt;- ggpredict(rq3a_brazil, terms = c(&quot;condition&quot;, &quot;Trust_SM&quot;))

rq3a_uk_plot &lt;- ggplot(rq3a_uk_results, aes(x, predicted, group=group)) +
   # geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
    ylab(&quot;accuracy&quot;) +
   #xlab(&quot;Condition&quot;) +
    ggtitle(&quot;UK&quot;) +
      scale_color_manual(&quot;Trust in social media&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.x=element_blank())

rq3a_brazil_plot &lt;- ggplot(rq3a_brazil_results, aes(x, predicted, group=group)) +
    #geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    #ylab(&quot;sharing&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;Brazil&quot;) +
      scale_color_manual(&quot;Trust in social media&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank())

rq3a_india_plot &lt;- ggplot(rq3a_india_results, aes(x, predicted, group=group)) +
    #geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    ylab(&quot;accuracy&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;India&quot;) +
      scale_color_manual(&quot;Trust in social media&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank(),
          axis.title.x=element_blank())

final_plot &lt;-rq3a_uk_plot + rq3a_brazil_plot + rq3a_india_plot + plot_layout(guides = &#39;collect&#39;)
print(final_plot)</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
<pre class="r"><code>ggsave(&quot;SMAcc.pdf&quot;, final_plot, width = 7, height = 5)</code></pre>
</div>
</div>
<div id="rq3b" class="section level2">
<h2>RQ3b</h2>
<div id="models-7" class="section level3">
<h3>Models</h3>
<pre class="r"><code># Is the effect of correction moderated by trust in Social Media?
rq3b_all &lt;- lmer(sharing ~ condition*Trust_SM + (1|post:country) + (1 | ResponseId) , data=subset(corrections_sharing_long))
summ(rq3b_all, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 12000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 28475.093, BIC = 28541.627
## Pseudo-R² (fixed effects) = 0.129
## Pseudo-R² (total) = 0.639 
## 
## FIXED EFFECTS:
## --------------------------------------------------------------------------------
##                                        Est.     2.5%   97.5%   t val.       d.f.
## ---------------------------------- -------- -------- ------- -------- ----------
## (Intercept)                           0.432    0.220   0.645    3.992     14.066
## conditioncorrection                  -0.088   -0.196   0.019   -1.605   2991.773
## conditionlink                        -0.066   -0.172   0.039   -1.231   2991.730
## Trust_SM                              0.318    0.279   0.358   15.728   3000.314
## conditioncorrection:Trust_SM         -0.005   -0.059   0.048   -0.193   2991.748
## conditionlink:Trust_SM               -0.023   -0.076   0.031   -0.831   2991.741
## --------------------------------------------------------------------------------
##  
## ------------------------------------------
##                                          p
## ---------------------------------- -------
## (Intercept)                          0.001
## conditioncorrection                  0.109
## conditionlink                        0.218
## Trust_SM                             0.000
## conditioncorrection:Trust_SM         0.847
## conditionlink:Trust_SM               0.406
## ------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.674   
##  post:country   (Intercept)     0.350   
##    Residual                     0.638   
## ----------------------------------------
## 
## Grouping variables:
## ---------------------------------
##     Group       # groups    ICC  
## -------------- ---------- -------
##   ResponseId      3000     0.461 
##  post:country      12      0.124 
## ---------------------------------</code></pre>
<pre class="r"><code>rq3b_uk &lt;- lmer(sharing ~ condition*Trust_SM + post + (1 | ResponseId) , data=subset(corrections_sharing_long, country==&quot;UK&quot;))
summ(rq3b_uk, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 6789.902, BIC = 6859.137
## Pseudo-R² (fixed effects) = 0.248
## Pseudo-R² (total) = 0.713 
## 
## FIXED EFFECTS:
## ----------------------------------------------------------------------
##                                        Est.     2.5%    97.5%   t val.
## ---------------------------------- -------- -------- -------- --------
## (Intercept)                           0.132    0.043    0.221    2.912
## conditioncorrection                  -0.024   -0.147    0.099   -0.385
## conditionlink                        -0.017   -0.136    0.102   -0.282
## Trust_SM                              0.385    0.323    0.446   12.253
## postfalse_2_sharing                  -0.083   -0.121   -0.045   -4.254
## postfalse_3_sharing                  -0.006   -0.044    0.032   -0.307
## postfalse_4_sharing                  -0.015   -0.053    0.023   -0.769
## conditioncorrection:Trust_SM         -0.005   -0.091    0.081   -0.111
## conditionlink:Trust_SM               -0.013   -0.098    0.072   -0.308
## ----------------------------------------------------------------------
##  
## -----------------------------------------------------
##                                          d.f.       p
## ---------------------------------- ---------- -------
## (Intercept)                          1145.469   0.004
## conditioncorrection                   994.000   0.700
## conditionlink                         994.000   0.778
## Trust_SM                              994.000   0.000
## postfalse_2_sharing                  2997.000   0.000
## postfalse_3_sharing                  2997.000   0.758
## postfalse_4_sharing                  2997.000   0.442
## conditioncorrection:Trust_SM          994.000   0.911
## conditionlink:Trust_SM                994.000   0.758
## -----------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.555   
##   Residual                    0.436   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.618 
## -------------------------------</code></pre>
<pre class="r"><code>rq3b_brazil &lt;- lmer(sharing ~ condition*Trust_SM + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;Brazil&quot;))
summ(rq3b_brazil, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9938.868, BIC = 10008.102
## Pseudo-R² (fixed effects) = 0.044
## Pseudo-R² (total) = 0.505 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------------
##                                        Est.     2.5%    97.5%    t val.
## ---------------------------------- -------- -------- -------- ---------
## (Intercept)                           0.740    0.591    0.888     9.781
## conditioncorrection                  -0.098   -0.302    0.106    -0.941
## conditionlink                        -0.080   -0.285    0.125    -0.762
## Trust_SM                              0.143    0.060    0.226     3.378
## postfalse_2_sharing                  -0.316   -0.376   -0.256   -10.306
## postfalse_3_sharing                  -0.397   -0.457   -0.337   -12.948
## postfalse_4_sharing                  -0.242   -0.302   -0.182    -7.893
## conditioncorrection:Trust_SM         -0.016   -0.133    0.100    -0.276
## conditionlink:Trust_SM               -0.002   -0.118    0.114    -0.032
## -----------------------------------------------------------------------
##  
## -----------------------------------------------------
##                                          d.f.       p
## ---------------------------------- ---------- -------
## (Intercept)                          1127.255   0.000
## conditioncorrection                   994.000   0.347
## conditionlink                         994.000   0.446
## Trust_SM                              994.000   0.001
## postfalse_2_sharing                  2997.000   0.000
## postfalse_3_sharing                  2997.000   0.000
## postfalse_4_sharing                  2997.000   0.000
## conditioncorrection:Trust_SM          994.000   0.783
## conditionlink:Trust_SM                994.000   0.975
## -----------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.661   
##   Residual                    0.686   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.482 
## -------------------------------</code></pre>
<pre class="r"><code>rq3b_india &lt;- lmer(sharing ~ condition*Trust_SM + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;India&quot;))
summ(rq3b_india, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10737.338, BIC = 10806.572
## Pseudo-R² (fixed effects) = 0.180
## Pseudo-R² (total) = 0.597 
## 
## FIXED EFFECTS:
## ----------------------------------------------------------------------
##                                        Est.     2.5%    97.5%   t val.
## ---------------------------------- -------- -------- -------- --------
## (Intercept)                           0.681    0.482    0.879    6.719
## conditioncorrection                  -0.259   -0.547    0.029   -1.763
## conditionlink                        -0.207   -0.487    0.072   -1.454
## Trust_SM                              0.343    0.268    0.418    8.971
## postfalse_2_sharing                   0.205    0.139    0.271    6.116
## postfalse_3_sharing                  -0.139   -0.205   -0.073   -4.147
## postfalse_4_sharing                   0.507    0.441    0.573   15.126
## conditioncorrection:Trust_SM          0.049   -0.059    0.157    0.888
## conditionlink:Trust_SM                0.012   -0.095    0.120    0.223
## ----------------------------------------------------------------------
##  
## -----------------------------------------------------
##                                          d.f.       p
## ---------------------------------- ---------- -------
## (Intercept)                          1080.228   0.000
## conditioncorrection                   994.000   0.078
## conditionlink                         994.000   0.146
## Trust_SM                              994.000   0.000
## postfalse_2_sharing                  2997.000   0.000
## postfalse_3_sharing                  2997.000   0.000
## postfalse_4_sharing                  2997.000   0.000
## conditioncorrection:Trust_SM          994.000   0.375
## conditionlink:Trust_SM                994.000   0.824
## -----------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.763   
##   Residual                    0.749   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.509 
## -------------------------------</code></pre>
</div>
<div id="plots-5" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>rq3b_uk_results &lt;- ggpredict(rq3b_uk, terms = c(&quot;condition&quot;, &quot;Trust_SM&quot;))
rq3b_india_results &lt;- ggpredict(rq3b_india, terms = c(&quot;condition&quot;, &quot;Trust_SM&quot;))
rq3b_brazil_results &lt;- ggpredict(rq3b_brazil, terms = c(&quot;condition&quot;, &quot;Trust_SM&quot;))

rq3b_uk_plot &lt;- ggplot(rq3b_uk_results, aes(x, predicted, group=group)) +
   # geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n likely&quot;, &quot;Not very\n likely&quot;, &quot;Somewhat\n likely&quot;, &quot;Very\n likely&quot;)) +
    ylab(&quot;Sharing&quot;) +
   #xlab(&quot;Condition&quot;) +
    ggtitle(&quot;UK&quot;) +
      scale_color_manual(&quot;Trust in social media&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.x=element_blank())

rq3b_brazil_plot &lt;- ggplot(rq3b_brazil_results, aes(x, predicted, group=group)) +
    #geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    #ylab(&quot;sharing&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;Brazil&quot;) +
      scale_color_manual(&quot;Trust in social media&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank())

rq3b_india_plot &lt;- ggplot(rq3b_india_results, aes(x, predicted, group=group)) +
    #geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    ylab(&quot;Sharing&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;India&quot;) +
      scale_color_manual(&quot;Trust in social media&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank(),
          axis.title.x=element_blank())



final_plot &lt;-rq3b_uk_plot + rq3b_brazil_plot + rq3b_india_plot + plot_layout(guides = &#39;collect&#39;)
print(final_plot)</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
<pre class="r"><code>ggsave(&quot;SMASha.pdf&quot;, final_plot, width = 7, height = 5)</code></pre>
</div>
</div>
<div id="rq4a" class="section level2">
<h2>RQ4a</h2>
<div id="models-8" class="section level3">
<h3>Models</h3>
<pre class="r"><code>rq4a_all &lt;- lmer(accuracy ~ condition*Trust_News + (1|post:country) + (1 | ResponseId) , data=subset(corrections_accuracy_long))
summ(rq4a_all, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 12000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 31585.713, BIC = 31652.247
## Pseudo-R² (fixed effects) = 0.005
## Pseudo-R² (total) = 0.507 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%   t val.
## ------------------------------------ -------- -------- -------- --------
## (Intercept)                             1.125    0.859    1.392    8.275
## conditioncorrection                    -0.144   -0.282   -0.006   -2.044
## conditionlink                          -0.195   -0.332   -0.058   -2.795
## Trust_News                              0.025   -0.017    0.066    1.179
## conditioncorrection:Trust_News          0.042   -0.016    0.100    1.430
## conditionlink:Trust_News                0.039   -0.017    0.096    1.354
## ------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                              14.581   0.000
## conditioncorrection                    2991.895   0.041
## conditionlink                          2991.920   0.005
## Trust_News                             2994.276   0.239
## conditioncorrection:Trust_News         2991.890   0.153
## conditionlink:Trust_News               2991.938   0.176
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.632   
##  post:country   (Intercept)     0.437   
##    Residual                     0.761   
## ----------------------------------------
## 
## Grouping variables:
## ---------------------------------
##     Group       # groups    ICC  
## -------------- ---------- -------
##   ResponseId      3000     0.341 
##  post:country      12      0.163 
## ---------------------------------</code></pre>
<pre class="r"><code>rq4a_uk &lt;- lmer(accuracy ~ condition*Trust_News + post + (1 | ResponseId) , data=subset(corrections_accuracy_long, country==&quot;UK&quot;))
summ(rq4a_uk, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9412.285, BIC = 9481.519
## Pseudo-R² (fixed effects) = 0.047
## Pseudo-R² (total) = 0.463 
## 
## FIXED EFFECTS:
## -------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%    t val.
## ------------------------------------ -------- -------- -------- ---------
## (Intercept)                             0.900    0.748    1.052    11.594
## conditioncorrection                    -0.013   -0.224    0.197    -0.125
## conditionlink                          -0.183   -0.389    0.024    -1.735
## Trust_News                             -0.018   -0.087    0.051    -0.515
## postfalse_2_accuracy                   -0.304   -0.361   -0.247   -10.408
## postfalse_3_accuracy                   -0.078   -0.135   -0.021    -2.670
## postfalse_4_accuracy                    0.226    0.169    0.283     7.737
## conditioncorrection:Trust_News          0.001   -0.098    0.101     0.029
## conditionlink:Trust_News                0.060   -0.037    0.156     1.216
## -------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                            1107.559   0.000
## conditioncorrection                     994.000   0.901
## conditionlink                           994.000   0.083
## Trust_News                              994.000   0.607
## postfalse_2_accuracy                   2997.000   0.000
## postfalse_3_accuracy                   2997.000   0.008
## postfalse_4_accuracy                   2997.000   0.000
## conditioncorrection:Trust_News          994.000   0.977
## conditionlink:Trust_News                994.000   0.224
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.575   
##   Residual                    0.653   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.436 
## -------------------------------</code></pre>
<pre class="r"><code>rq4a_brazil &lt;- lmer(accuracy ~ condition*Trust_News + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;Brazil&quot;))
summ(rq4a_brazil, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10872.058, BIC = 10941.293
## Pseudo-R² (fixed effects) = 0.095
## Pseudo-R² (total) = 0.331 
## 
## FIXED EFFECTS:
## -------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%    t val.
## ------------------------------------ -------- -------- -------- ---------
## (Intercept)                             1.745    1.604    1.887    24.165
## conditioncorrection                    -0.217   -0.407   -0.028    -2.249
## conditionlink                          -0.212   -0.405   -0.020    -2.163
## Trust_News                             -0.160   -0.221   -0.099    -5.148
## postfalse_2_accuracy                   -0.501   -0.574   -0.428   -13.373
## postfalse_3_accuracy                   -0.783   -0.856   -0.710   -20.901
## postfalse_4_accuracy                   -0.363   -0.436   -0.290    -9.690
## conditioncorrection:Trust_News          0.071   -0.015    0.158     1.620
## conditionlink:Trust_News                0.065   -0.020    0.151     1.493
## -------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                            1224.446   0.000
## conditioncorrection                     994.000   0.025
## conditionlink                           994.000   0.031
## Trust_News                              994.000   0.000
## postfalse_2_accuracy                   2997.000   0.000
## postfalse_3_accuracy                   2997.000   0.000
## postfalse_4_accuracy                   2997.000   0.000
## conditioncorrection:Trust_News          994.000   0.105
## conditionlink:Trust_News                994.000   0.136
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.497   
##   Residual                    0.838   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.261 
## -------------------------------</code></pre>
<pre class="r"><code>rq4a_india &lt;- lmer(accuracy ~ condition*Trust_News + post + (1 | ResponseId), data=subset(corrections_accuracy_long, country==&quot;India&quot;))
summ(rq4a_india, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10916.243, BIC = 10985.477
## Pseudo-R² (fixed effects) = 0.149
## Pseudo-R² (total) = 0.540 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%   t val.
## ------------------------------------ -------- -------- -------- --------
## (Intercept)                             0.802    0.556    1.049    6.371
## conditioncorrection                    -0.190   -0.526    0.146   -1.109
## conditionlink                          -0.122   -0.449    0.204   -0.733
## Trust_News                              0.273    0.186    0.359    6.193
## postfalse_2_accuracy                    0.227    0.159    0.295    6.495
## postfalse_3_accuracy                   -0.226   -0.294   -0.158   -6.467
## postfalse_4_accuracy                    0.628    0.560    0.696   17.970
## conditioncorrection:Trust_News          0.050   -0.070    0.170    0.816
## conditionlink:Trust_News               -0.012   -0.128    0.104   -0.203
## ------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                            1053.665   0.000
## conditioncorrection                     994.000   0.268
## conditionlink                           994.000   0.464
## Trust_News                              994.000   0.000
## postfalse_2_accuracy                   2997.000   0.000
## postfalse_3_accuracy                   2997.000   0.000
## postfalse_4_accuracy                   2997.000   0.000
## conditioncorrection:Trust_News          994.000   0.415
## conditionlink:Trust_News                994.000   0.839
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.721   
##   Residual                    0.781   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.460 
## -------------------------------</code></pre>
</div>
<div id="plots-6" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>rq4a_uk_results &lt;- ggpredict(rq4a_uk, terms = c(&quot;condition&quot;, &quot;Trust_News&quot;))
rq4a_india_results &lt;- ggpredict(rq4a_india, terms = c(&quot;condition&quot;, &quot;Trust_News&quot;))
rq4a_brazil_results &lt;- ggpredict(rq4a_brazil, terms = c(&quot;condition&quot;, &quot;Trust_News&quot;))


rq4a_uk_plot &lt;- ggplot(rq4a_uk_results, aes(x, predicted, group=group)) +
   # geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
    ylab(&quot;accuracy&quot;) +
   #xlab(&quot;Condition&quot;) +
    ggtitle(&quot;UK&quot;) +
      scale_color_manual(&quot;Trust in news&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.x=element_blank())

rq4a_brazil_plot &lt;- ggplot(rq4a_brazil_results, aes(x, predicted, group=group)) +
    #geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    #ylab(&quot;sharing&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;Brazil&quot;) +
      scale_color_manual(&quot;Trust in news&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank())

rq4a_india_plot &lt;- ggplot(rq4a_india_results, aes(x, predicted, group=group)) +
   # geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    ylab(&quot;accuracy&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;India&quot;) +
      scale_color_manual(&quot;Trust in news&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank(),
          axis.title.x=element_blank())

final_plot &lt;-rq4a_uk_plot + rq4a_brazil_plot + rq4a_india_plot + plot_layout(guides = &#39;collect&#39;)
print(final_plot)</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
<pre class="r"><code>ggsave(&quot;TrustAcc.pdf&quot;, final_plot, width = 7, height = 5)</code></pre>
</div>
</div>
<div id="rq4b" class="section level2">
<h2>RQ4b</h2>
<div id="models-9" class="section level3">
<h3>Models</h3>
<pre class="r"><code># Is the effect of correction moderated by trust in Social Media?
rq4b_all &lt;- lmer(sharing ~ condition*Trust_News + (1|post:country) + (1 | ResponseId) , data=subset(corrections_sharing_long))
summ(rq4b_all, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 12000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 28948.410, BIC = 29014.944
## Pseudo-R² (fixed effects) = 0.017
## Pseudo-R² (total) = 0.661 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%   t val.
## ------------------------------------ -------- -------- -------- --------
## (Intercept)                             0.732    0.440    1.023    4.924
## conditioncorrection                    -0.149   -0.300    0.002   -1.937
## conditionlink                          -0.177   -0.327   -0.028   -2.320
## Trust_News                              0.092    0.046    0.137    3.966
## conditioncorrection:Trust_News          0.041   -0.022    0.104    1.278
## conditionlink:Trust_News                0.038   -0.024    0.100    1.213
## ------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                              14.513   0.000
## conditioncorrection                    2991.815   0.053
## conditionlink                          2991.840   0.020
## Trust_News                             2994.215   0.000
## conditioncorrection:Trust_News         2991.810   0.201
## conditionlink:Trust_News               2991.859   0.225
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.740   
##  post:country   (Intercept)     0.478   
##    Residual                     0.638   
## ----------------------------------------
## 
## Grouping variables:
## ---------------------------------
##     Group       # groups    ICC  
## -------------- ---------- -------
##   ResponseId      3000     0.463 
##  post:country      12      0.193 
## ---------------------------------</code></pre>
<pre class="r"><code>rq4b_uk &lt;- lmer(sharing ~ condition*Trust_News + post + (1 | ResponseId) , data=subset(corrections_sharing_long, country==&quot;UK&quot;))
summ(rq4b_uk, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 7146.174, BIC = 7215.408
## Pseudo-R² (fixed effects) = 0.018
## Pseudo-R² (total) = 0.713 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%   t val.
## ------------------------------------ -------- -------- -------- --------
## (Intercept)                             0.367    0.205    0.528    4.450
## conditioncorrection                    -0.053   -0.280    0.175   -0.454
## conditionlink                          -0.153   -0.376    0.070   -1.346
## Trust_News                              0.067   -0.008    0.141    1.749
## postfalse_2_sharing                    -0.083   -0.121   -0.045   -4.254
## postfalse_3_sharing                    -0.006   -0.044    0.032   -0.307
## postfalse_4_sharing                    -0.015   -0.053    0.023   -0.769
## conditioncorrection:Trust_News          0.025   -0.082    0.132    0.453
## conditionlink:Trust_News                0.060   -0.044    0.164    1.130
## ------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                            1037.036   0.000
## conditioncorrection                     993.999   0.650
## conditionlink                           993.999   0.179
## Trust_News                              993.999   0.081
## postfalse_2_sharing                    2997.000   0.000
## postfalse_3_sharing                    2997.000   0.758
## postfalse_4_sharing                    2997.000   0.442
## conditioncorrection:Trust_News          993.999   0.650
## conditionlink:Trust_News                993.999   0.259
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.679   
##   Residual                    0.436   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.708 
## -------------------------------</code></pre>
<pre class="r"><code>rq4b_brazil &lt;- lmer(sharing ~ condition*Trust_News + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;Brazil&quot;))
summ(rq4b_brazil, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9960.466, BIC = 10029.701
## Pseudo-R² (fixed effects) = 0.032
## Pseudo-R² (total) = 0.505 
## 
## FIXED EFFECTS:
## -------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%    t val.
## ------------------------------------ -------- -------- -------- ---------
## (Intercept)                             1.141    0.981    1.301    14.016
## conditioncorrection                    -0.233   -0.452   -0.014    -2.083
## conditionlink                          -0.188   -0.411    0.034    -1.660
## Trust_News                             -0.105   -0.175   -0.034    -2.921
## postfalse_2_sharing                    -0.316   -0.376   -0.256   -10.306
## postfalse_3_sharing                    -0.397   -0.457   -0.337   -12.948
## postfalse_4_sharing                    -0.242   -0.302   -0.182    -7.893
## conditioncorrection:Trust_News          0.063   -0.037    0.163     1.233
## conditionlink:Trust_News                0.065   -0.034    0.164     1.291
## -------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                            1107.657   0.000
## conditioncorrection                     994.000   0.038
## conditionlink                           994.000   0.097
## Trust_News                              994.000   0.004
## postfalse_2_sharing                    2997.000   0.000
## postfalse_3_sharing                    2997.000   0.000
## postfalse_4_sharing                    2997.000   0.000
## conditioncorrection:Trust_News          994.000   0.218
## conditionlink:Trust_News                994.000   0.197
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.669   
##   Residual                    0.686   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.488 
## -------------------------------</code></pre>
<pre class="r"><code>rq4b_india &lt;- lmer(sharing ~ condition*Trust_News + post + (1 | ResponseId), data=subset(corrections_sharing_long, country==&quot;India&quot;))
summ(rq4b_india, digits=3, confint =T)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 4000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 10807.869, BIC = 10877.103
## Pseudo-R² (fixed effects) = 0.142
## Pseudo-R² (total) = 0.597 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                          Est.     2.5%    97.5%   t val.
## ------------------------------------ -------- -------- -------- --------
## (Intercept)                             0.590    0.326    0.855    4.377
## conditioncorrection                    -0.129   -0.490    0.232   -0.702
## conditionlink                          -0.147   -0.498    0.204   -0.823
## Trust_News                              0.333    0.241    0.426    7.048
## postfalse_2_sharing                     0.205    0.139    0.271    6.116
## postfalse_3_sharing                    -0.139   -0.205   -0.073   -4.147
## postfalse_4_sharing                     0.507    0.441    0.573   15.126
## conditioncorrection:Trust_News          0.028   -0.100    0.157    0.433
## conditionlink:Trust_News               -0.004   -0.128    0.120   -0.061
## ------------------------------------------------------------------------
##  
## -------------------------------------------------------
##                                            d.f.       p
## ------------------------------------ ---------- -------
## (Intercept)                            1041.481   0.000
## conditioncorrection                     994.000   0.483
## conditionlink                           994.000   0.411
## Trust_News                              994.000   0.000
## postfalse_2_sharing                    2997.000   0.000
## postfalse_3_sharing                    2997.000   0.000
## postfalse_4_sharing                    2997.000   0.000
## conditioncorrection:Trust_News          994.000   0.665
## conditionlink:Trust_News                994.000   0.951
## -------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.797   
##   Residual                    0.749   
## --------------------------------------
## 
## Grouping variables:
## -------------------------------
##    Group      # groups    ICC  
## ------------ ---------- -------
##  ResponseId     1000     0.531 
## -------------------------------</code></pre>
</div>
<div id="plots-7" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>rq4b_uk_results &lt;- ggpredict(rq4b_uk, terms = c(&quot;condition&quot;, &quot;Trust_News&quot;))
rq4b_india_results &lt;- ggpredict(rq4b_india, terms = c(&quot;condition&quot;, &quot;Trust_News&quot;))
rq4b_brazil_results &lt;- ggpredict(rq4b_brazil, terms = c(&quot;condition&quot;, &quot;Trust_News&quot;))

rq4b_uk_plot &lt;- ggplot(rq4b_uk_results, aes(x, predicted, group=group)) +
    #geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n likely&quot;, &quot;Not very\n likely&quot;, &quot;Somewhat\n likely&quot;, &quot;Very\n likely&quot;)) +
    ylab(&quot;Sharing&quot;) +
   #xlab(&quot;Condition&quot;) +
    ggtitle(&quot;UK&quot;) +
      scale_color_manual(&quot;Trust in news&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.x=element_blank())

rq4b_brazil_plot &lt;- ggplot(rq4b_brazil_results, aes(x, predicted, group=group)) +
   # geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    #ylab(&quot;sharing&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;Brazil&quot;) +
      scale_color_manual(&quot;Trust in news&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank())

rq4b_india_plot &lt;- ggplot(rq4b_india_results, aes(x, predicted, group=group)) +
    #geom_line(aes(color=group)) +
    geom_point(aes(color=group)) +
    geom_errorbar(aes(ymin=conf.low, ymax=conf.high, color=group), width=.1) +
    scale_x_discrete(labels=c(&quot;Control&quot;,&quot;No link&quot;,&quot;Link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
    ylab(&quot;Sharing&quot;) +
    xlab(&quot;Condition&quot;) +
    ggtitle(&quot;India&quot;) +
      scale_color_manual(&quot;Trust in news&quot;, 
                      values = c(&quot;#d7eefd&quot;, &quot;#99c8ff&quot;, &quot;#55a7ff&quot;, &quot;#1f86ff&quot;, &quot;#0d42ff&quot;), 
                      labels = c(&quot;Not at all&quot;, &quot;A little&quot;, &quot;A moderate amount&quot;, &quot;A lot&quot;, &quot;A great deal&quot;))+
    theme_classic() +
    theme(axis.title.y=element_blank(),
          axis.text.y=element_blank(),
          axis.title.x=element_blank())

final_plot &lt;-rq4b_uk_plot + rq4b_brazil_plot + rq4b_india_plot + plot_layout(guides = &#39;collect&#39;)
print(final_plot)</code></pre>
<p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABUAAAAPACAYAAAD0ZtPZAAAEDmlDQ1BrQ0dDb2xvclNwYWNlR2VuZXJpY1JHQgAAOI2NVV1oHFUUPpu5syskzoPUpqaSDv41lLRsUtGE2uj+ZbNt3CyTbLRBkMns3Z1pJjPj/KRpKT4UQRDBqOCT4P9bwSchaqvtiy2itFCiBIMo+ND6R6HSFwnruTOzu5O4a73L3PnmnO9+595z7t4LkLgsW5beJQIsGq4t5dPis8fmxMQ6dMF90A190C0rjpUqlSYBG+PCv9rt7yDG3tf2t/f/Z+uuUEcBiN2F2Kw4yiLiZQD+FcWyXYAEQfvICddi+AnEO2ycIOISw7UAVxieD/Cyz5mRMohfRSwoqoz+xNuIB+cj9loEB3Pw2448NaitKSLLRck2q5pOI9O9g/t/tkXda8Tbg0+PszB9FN8DuPaXKnKW4YcQn1Xk3HSIry5ps8UQ/2W5aQnxIwBdu7yFcgrxPsRjVXu8HOh0qao30cArp9SZZxDfg3h1wTzKxu5E/LUxX5wKdX5SnAzmDx4A4OIqLbB69yMesE1pKojLjVdoNsfyiPi45hZmAn3uLWdpOtfQOaVmikEs7ovj8hFWpz7EV6mel0L9Xy23FMYlPYZenAx0yDB1/PX6dledmQjikjkXCxqMJS9WtfFCyH9XtSekEF+2dH+P4tzITduTygGfv58a5VCTH5PtXD7EFZiNyUDBhHnsFTBgE0SQIA9pfFtgo6cKGuhooeilaKH41eDs38Ip+f4At1Rq/sjr6NEwQqb/I/DQqsLvaFUjvAx+eWirddAJZnAj1DFJL0mSg/gcIpPkMBkhoyCSJ8lTZIxk0TpKDjXHliJzZPO50dR5ASNSnzeLvIvod0HG/mdkmOC0z8VKnzcQ2M/Yz2vKldduXjp9bleLu0ZWn7vWc+l0JGcaai10yNrUnXLP/8Jf59ewX+c3Wgz+B34Df+vbVrc16zTMVgp9um9bxEfzPU5kPqUtVWxhs6OiWTVW+gIfywB9uXi7CGcGW/zk98k/kmvJ95IfJn/j3uQ+4c5zn3Kfcd+AyF3gLnJfcl9xH3OfR2rUee80a+6vo7EK5mmXUdyfQlrYLTwoZIU9wsPCZEtP6BWGhAlhL3p2N6sTjRdduwbHsG9kq32sgBepc+xurLPW4T9URpYGJ3ym4+8zA05u44QjST8ZIoVtu3qE7fWmdn5LPdqvgcZz8Ww8BWJ8X3w0PhQ/wnCDGd+LvlHs8dRy6bLLDuKMaZ20tZrqisPJ5ONiCq8yKhYM5cCgKOu66Lsc0aYOtZdo5QCwezI4wm9J/v0X23mlZXOfBjj8Jzv3WrY5D+CsA9D7aMs2gGfjve8ArD6mePZSeCfEYt8CONWDw8FXTxrPqx/r9Vt4biXeANh8vV7/+/16ffMD1N8AuKD/A/8leAvFY9bLAAAAOGVYSWZNTQAqAAAACAABh2kABAAAAAEAAAAaAAAAAAACoAIABAAAAAEAAAVAoAMABAAAAAEAAAPAAAAAALYRw1EAAEAASURBVHgB7N0HnFXF3TDgwS6CFVRUxIYdo2KLNfaCLZaQN8UWo76ixJJi1M+SqK8tiRprjCYxMXajaOwFG8aIvWAjWNDYO9jl2/8k53p39y7sHkAPu8/8fpd7ysw5c55ZLuz/Tuk2oSkliQABAgQIECBAgAABAgQIECBAgAABAp1QYLpO+EweiQABAgQIECBAgAABAgQIECBAgAABAllAANQPAgECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZAALTTNq0HI0CAAAECBAgQIECAAAECBAgQIEBAANTPAAECBAgQIECAAAECBAgQIECAAAECnVZghk77ZB6MQBsC48aNS08++WTt7IABA9KMM85Y22/PxtNPP53ee++9nLV3796pb9++rYq99tpr6YUXXsjH4/pxn46kMWPGpLfeeqtWZJZZZknLLrtsbd8GAQLVE6j/ez+x2s0666xpnnnmSXPPPXeaYYau809x/edafG7G52d9qv9sXXTRRdNcc81Vf9o2gS4t8Mwzz6R33303G8TnR79+/Srj8fnnn6cHH3ywVp+VVlopdevWrbYfG5P6+98ssx0CBAgQIECAwBQW6DahKU3ha7ocgUoL3HXXXWnttdeu1fGll15Kffr0qe23Z2P99ddPw4cPz1n33nvvdNppp7UqFsf22WeffHzeeedNr7zySqs8bR24+uqr0/bbb58+/vjjnKV79+5p2LBhacMNN2yriOMECFRAoP7vfXuqE8HPr3/962mrrbZKQ4YMSfF3vTOnwYMHp4svvjg/4sknn5yGDh3a7HHrP1svuOCC9O1vf7vZeTsEurLA5ptvnq677rpMsNtuu6VzzjmnMhzx5XKPHj1q9fnggw9SfHFbnyb1978+r20CBAgQIECAwJQWMAR+Sou6HoHJFLjqqquaBT979uyZf+ER/JxMWMUJVFDg008/TXfccUf66U9/mpZffvk0cuTICtZSlQgQIECAAAECBAgQIDBtC3SdcXfTdjupfRcRiODnDjvsUOv5Oeecc+bg5+qrr95FBDwmgc4jEFNfrLLKKq0eKHp2R++oN954o1nP8BgeOmjQoPTPf/6zUkNbWz2AAwQIECBAgAABAgQIEJjGBARAp7EGU93OK9Ay+Bnze914440p5tGSCBCY9gRi/soRI0ZMtOIvv/xynirjsssuy/leffXV9LOf/SxdeOGFEy03rZ6MaUFiuH+kVVdddVp9DPUmQKCEgL//JdAUIUCAAAECBKaYgADoFKN0IQLlBVoGP+ebb75000035SGx5a+qJAECVReYf/7506WXXpqDoMVcwrEfgdE419nSOuusk+IlESDQ9QT8/e96be6JCRAgQIBAlQTMAVql1lCXLikQixvVD3tfcMEF02233Sb42SV/Gjx0VxXYeeeda4/+2WefpYcffri2b4MAAQIECBAgQIAAAQIEJk9AD9DJ81OawGQJRPBzxx13rM352a9fv3TLLbekxRZbbLKuqzABAtOWwMCBA9Oss86a5waNmr/11lutHiCCom+++WY+vvbaa6dYQf7BBx9MV1xxRZ5L9Gtf+1r6zne+k2afffZWZePACy+8kJ544on8evLJJ9O7776bYp7hRRddNH3jG99oc7qNKBM9UsukAQMGpJjOo0iPP/54imH+kfr375/iCx+JAIEpJ/Doo4+m119/PV9wzTXXTDPNNFPefu655/KUHHfffXeK+YlXXnnlFJ87Sy+9dLtvftddd+VF20aPHp169eqVe3PHPeJzpD2po3//y35mtacu8hAgQIAAAQJdT0AAtOu1uSeuiEDL4OcSSyyRbr755rTwwgtXpIaqQYDAlyXwzDPP1IKfcc/FF1+81a0POuigdO211+bjEQg9+eST05FHHtks389//vMUiynVBySuvPLKdNhhh02yV+k222yTTj/99LTAAgs0u+Zxxx2X/vjHPzY71t6dq6++Oi/sVOSP+l588cV5N+o/dOjQ4pR3AgSmgMDhhx+eLr/88nylF198MX9RsuWWW6Z777234dUHDx6czj777NSzZ8+G5+PgyJEj07777pv+8Y9/NMtz7LHHpumnnz6dcsopqb4Xe7NMdTvt/fs/uZ9Zdbe0SYAAAQIECBCoCRgCX6OwQeDLE2g57H2ZZZbJw94FP7+8NnAnAlUSiF/4ixQ9I6N31sTSNddc0yr4GfmXW265ZsHPY445Jm277bbNgp/TTTdd7pUZ7/Up6rDsssumsWPH1h+erO3oaSYRIPDVCDz77LMpeou3FfyMWl100UW5J+jbb7/dsJLXX3997iFeH/zs1q1b6t69e84fU3YMGTIk/eQnP2lYvqMHv+rPrI7WV34CBAgQIEBg2hFo/tvPtFNvNSUwzQpEkCHm/Pzkk0/yM6ywwgpp+PDhrXpdTbMPqOIECLRb4MMPP0zRazNekSKwED0uWwYnW15w//33z4d69OiRvvWtb6XNNtsszTzzzM16YUWv0v/3//5frej//M//5CHzH3/8cR4iG/d+7LHH0m677Va73zvvvJNOOumkWpnYiFXpY2qOtl533HFHDrBE79T6XmTf/OY300YbbdTsWnYIEPjyBAYNGpSefvrpPN3E+eefn5566qk8nUUEPTfddNNaRSLPueeeW9svNl566aW0/fbbp3HjxuVDCy20UIr/w8QUHe+9917+PNl1113zuTPOOKMoVvp9Sn1mla6AggQIECBAgECnFjAEvlM3r4ermkD84hBzfhbBz6hfrPjeu3fvqlVVfQgQmEyBmGNz9913b3WVCRMmpPHjx6c33ngjBxBee+21nCfm9DzxxBNTBA4nlaLMaqutlr88iblDI0WQIoajFunUU09Nn3/+ed6Nz52//vWvxan8Hr0zo8fnOeeck+fzO/744/Px2I96FCnmCJzUPIERDIlnjfdIq6yySvrLX/5SC6wW1/JOgMCXJxC9OjfZZJN01VVX1eYCjbvHlyYx5UV8QXHnnXfmCkUA84ADDmhWuZh2owh+xkiVW2+9Nf+fpcgU8w5H4DTO/fSnPy0Ol36fUp9ZpSugIAECBAgQINCpBQRAO3XzergqCTQKfkb9brzxxtzjK37RkAgQ6DwC0cMygontSdHj88ILL8y9rdqTP3p7/ulPf8oLJxX5Z5tttmIzBy3+8Ic/1PaPOOKI2najjV122SUVAdAImkQgs743Z6MyxbFPP/00f7Hz0EMP5UN9+/ZNMc1HMUS2yOedAIEvVyAWQIqgYrEQUv3d4zPkN7/5TVp11VXz4eh9GT3A55hjjrwfnwP1X5r88pe/bBb8rL9WDH+PLzxiobayKQKtX9ZnVtk6KkeAAAECBAhM2wKGwE/b7af204hADBer7/m54YYbplg5tUgxTDVWZpUIEOiaAtFTMxYjiZ5ZRY/QiUksv/zyE+2VGcHQWAAlVomPoenR03NiaZFFFml2OoK37U3/+7//m2KewEgRNI2Fj/r06dPe4vIRIDCVBL7xjW/k4e9tXT56cNan+nlA4+90zO8Zackll5xkz/SDDz64/lId3v4yP7M6XDkFCBAgQIAAgU4hoAdop2hGD1F1gfoh7zFX39/+9rcUc2utuOKKuadV9KAq5uerX7256s+lfgQItC0w++yz595XjXJ88MEH+e9+zL138803p+h9FcGGSy65JPeiip7h0ZOyrbTEEku0dap2POYHjQBHyyBHLUPTRtzz/vvvz3WoPx6fSe1JRx99dPr973+fs8bw++jFGvMaSwQIfPUCLb/YaFmjmAYjptCIz6NIMT9wkWJu3yLFlBaTmpc4vtid3PRlfGZNbh2VJ0CAAAECBKZdAQHQabft1LykQP0ceXGJoodDRy5X/0tCy+tN7DpbbbVVDnDE0LPFFlssnXLKKalYQOC5555LP/jBD9Jll102sUs4R4DANCIwyyyzpO9///uTrO1HH32U58+Lz4NITz75ZNp7773zvH1tFY6V4juS4h7RGzQWPYpgayyGEveJ7Ua9PWOe0kmlWFTl0EMPrWWLxZO22GKL2r4NAgS+WoF+/fpNsgIxPL4IgBZzBkehl19+uVY2Fj+aVOrVq1eKz7xGnyeTKtvo/NT4zGp0H8cIECBAgACBriMgANp12tqT/legZQ/LYtGOjgDV/2JQzJc1qfLbbbdd7h0VPS6KFPPuxXDRIuh5+eWXp9NPPz0HP4o83gkQ6NwC8YXIySefnOfMPPbYY/PDxufCfffdlwYOHNjw4dsT2IiCMZw+5gCMz5XXX3+94bXiYAw/LRY7aTNT3Ynbbrstrx5fHNp3333TPvvsU+x6J0CgAgJzzTVX6Vq8+uqrtbLtCYBG5sgXX6pMTppan1mTUydlCRAgQIAAgc4hIADaOdrRU3RAYO65526WO1Zq7mj697//XSvSMqBaO1G3Eb+EXHTRRSlWeW6Zfve73+X5P2NIfKQDDzwwrb322oaRtoSyT6CTC+ywww6pCIDGo44YMaLNAGh7ep6/8MIL6etf/3qeC7Ql3fzzz5+Hxsdw9Q022CDPSVz/ZU63bt1aFqntjxo1Ks8HWPSEHzRoUF5MpZbBBgEC07xA/Ze10RuzPSm+zJmcNLU+syanTsoSIECAAAECnUegdTSm8zybJyHQUKBlj4ixY8em1VdfvWHeRgdjldRiuFicbxlQbVQmfpFoFPwsyv/xj39Mm266aYphpzF8LBZDGTlyZO6V1eh6jhEg0PkEVl555fx58uabb+aHGzNmTOmHfP/991PMNxwLIUWKz6Dopbn55pvnwGfv3r2bXbt+8ZM40dYQ+FdeeSUPc4+F3SLF/KIx72d7ArK5gD8IEJgmBOoXMospetqTnn/++fZka5hnan1mNbyZgwQIECBAgECXFLAKfJds9q790BEIWGqppWoI0cuqIynm0atPK620Uv1uqe2NN944DR06tFb2iSeeMJy0pmGDQNcQiABAfMFSpMUXX7zY7PD7Lbfckh5//PFcLr58uemmm9KvfvWrtNFGG6WWwc/I9MYbbzS7R6NFkMaPH5+23HLL9Oyzz+a8ESCJofqxcIlEgEDnEqifZqM9AdD4UqTMlEKF2tT4zCqu7Z0AAQIECBAgEAICoH4OuqRABAGKFPNudmTS/uOPP74ommL4+5Ra8TiGvi633HK1a0ev0L/85S+1fRsECHRugbvuuqvZomxrrrlm6QcePnx4rWxMqbHuuuvW9htt3H333c0Ot1wcLva//e1v557pkbF79+55kab2zg3Y7OJ2CBCovED9gma33nrrROcQjoe58cYbJ+uZpvRn1mRVRmECBAgQIECgUwoIgHbKZvVQkxKIoaFFit5MBx10ULE70ffoLXrNNdfU8sSq7tNNN2X+GsXqqbGqcqzIWqRYCfrpp58udr0TINBJBWJe4fj7XqToVTk5X64UcwrH9eabb77isg3fY1j7L3/5y2bnWvYA/dGPflRblT6Gu//1r39tc37SZheyQ4DANCkQX8AssMACue7RO/2EE05o8zli9fgjjzyyzfPtOTGlP7Pac095CBAgQIAAga4lMGUiN13LzNN2AoEYxvmNb3yj9iSxAnMsQBJDzxul+M//z372s2ZlYtXkY445plH20sdiPr2jjz66Vj6Gk0Wvq/YuQFAraIMAgcoLRNDgX//6VzruuOPSWmutlern/DziiCMma17N+CwpUgx/r1+4rTge7zHfaEzB8dRTT9UfbjaUNYbOn3baabXzsaL8NttsU9u3QYBA5xOIhdCOOuqo2oPF/5Pii4+WKb4s2W+//WpTbrQ83979KfmZ1d57ykeAAAECBAh0LYEZutbjeloCXwicddZZadVVV03FKvCXXXZZilf8Jzzm3ovFjWKBpAhQRC/RYsXjuEL0+jzllFPS1Bj+GavARy/TGHIW6f77708//elPU/zyIREgMO0IvPrqq6mtVZEj+Nmyl2XxZN/61rdSfA5MTooAZfTIii9PYn7P9ddfP3+5ssYaa+Re5nfeeWe67bbb0rBhw3LgNYId8aVOfNkT6bXXXsvv99xzT/rJT36St+OPRRddNAdLo7dqzAkaC8K1tWBS5F9wwQWtEB8QEoFpUGDXXXfNQc/4EiU+S7773e/moe7xJfJiiy2WHnjggRTT9dxxxx35/0XxeVe/SGRHHnlKfWZ15J7yEiBAgAABAl1LQAC0a7W3p60TWHLJJfN8dtttt1169NFHa2ceeuihFK+2UgxNjVWPBw0a1FaWyToegYjzzjsvDRgwIBUrM0ewdcMNN0xbb731ZF1bYQIEvlyB+i9OJnXn+Gz5wQ9+0KwX+KTKtHV+2WWXTTFfcQxdj/Tkk0/mXu6N8vfq1SsHMSLIcdJJJ+Ussb3pppuml19+uVmAM3qpRo/Q9qall15aALS9WPIRqKDAFVdckeJLmWL6nwh4xqs+xeKSMWd59FwfNWpU/al2b0+pz6x231BGAgQIECBAoMsJGALf5ZrcA9cL9O/fP0UPpzPOOCPFQiERfGwrxYqoMRws5uScWsHP4t7RszTqVJ+iJ8YLL7xQf8g2AQLTqEDM+Rs9qNZZZ500ePDgPL9e/P2OAGT0xJwSaejQoTloEYGFRqlv377p4IMPzsHR+EzbZJNNatkuuOCCFL1UJQIEurZAfB5deeWV6be//W2qXxm+UIn/R/3tb3/LQdLiWNl3n1ll5ZQjQIAAAQIE2iPQrWno2oT2ZJSHQFcQiMVAYrh79HqK7Z49e+Zh7jGMc5FFFpliCx51BUvPSIBANQQikBmfa6NHj06x0EhM8bH88sunOeecsxoVVAsCBKYJgZi2I0bMxBfBsWBjLJTUu3fvKV53n1lTnNQFCRAgQIAAgSYBAdAu+mNw4okn5gV/VltttbTHHntMUuGzzz5L+++/f57zbciQIWmllVaaZBkZCBAgQIAAAQIECBAgQIAAAQIECHzVAobAf9Ut8BXdf6mllsrDHi+//PJ2rTB+77335snuo/fQcsst9xXV2m0JECBAgAABAgQIECBAgAABAgQIdExAALRjXp0mdyyoE3PQjRs3Lo0YMWKSz3XdddflPLEoRgx7kggQIECAAAECBAgQIECAAAECBAhMCwICoNNCK02FOnbv3j1tsMEG+co33HDDRO/w/vvvpzvuuCPn2XLLLSea10kCBAgQIECAAAECBAgQIECAAAECVRKYoUqVUZcvVyBW/b3mmmvSP/7xj/Tuu++m2WefvWEFbrnllvTxxx+nZZZZJi+e0TJTTFYfqxc/88wzKeYKjRVBF1544TT99NO3zJrefvvt9NZbb6VevXrlHqj33XdfinW4VlxxxbzwUBSIlYlnmKH1j2bc57nnnsvXXHTRRVtd2wECBAgQIECAAAECBAgQIECAAAECLQVaR5la5rDfaQVWWGGFHKh8/vnn06233pq22Wabhs967bXX5uNbbbVVq/NjxoxJRx55ZF5duP5kBCgPO+ywtMQSS9QfTldddVX63e9+lw488MAU13388cfz+TnmmCNFr9R///vf6YgjjkgxRL9linlIf/zjH+c5SM8888yWp+0TIECAAAECBAgQIECAAAECBAgQaCVgCHwrkq51oBjSfv311zd88OjZ+eijj6ZZZ521VVBy1KhRaffdd8/Bz/XWWy8HPA8//PC02WabpQiMxuryTz75ZMPrXnTRRTn4GYHSBRZYIK288sppiy22yHnbGpJfzEO6+eabN7ymgwQIECBAgAABAgQIECBAgAABAgRaCugB2lKki+1HsPKss85KjzzySB6CPv/88zcTKIKOMV9o9NAsUgxbP+mkk/LQ+N122y3tuuuuxam00UYb5aHyp512Ws5zxhln1M4VG2PHjk1Dhw5NO+64Yz700Ucf5eHx5557brrnnnvy9pxzzllkT+PHj0+33357XoCpUe/QWkYbBAgQIECAAAECBAgQIECAAAECBOoE9ACtw+iKm3PNNVdac80186O37HkZQc6iZ2jL4e8PPPBA7sEZc3nutNNOrei23nrrHKyM3qOPPfZYq/PzzDNP2mGHHWrHZ5555jTffPOlgQMH5nlEY97R+hRD9GMe0nXWWSf16NGj/pRtAgQIECBAgAABAgQIECBAgAABAm0KCIC2SdN1ThTD4G+88cZmDx1BzldeeSXFMPXllluu2blnn3027/fp0yc9/PDDKfLWv2Loe7FQUbFwUf0FYqGjbt261R/K28Uw+CLwWmQoeqIa/l6IeCdAgAABAgQIECBAgAABAgQIEGiPgCHw7VHq5HlWX331vCp7BDWfeuqptOSSS+YnntjiRzE3aKQYOh9D2SeWXnzxxVanY97PRmnddddNs802W+5dGuUWXHDBHIR98MEHcx1XWWWVRsUcI0CAAAECBAgQIECAAAECBAgQINBQQAC0IUvXOjj99NOn6Fn55z//OcUw+AiAxpybw4cPTzPOOGPaZJNN2gRZaaWV0lprrdXm+ThRBFTrM80000z1u7XtGAofc3wOGzYsD7+P+UWL3p+bbrppirpKBAgQIECAAAECBAgQIECAAAECBNorIADaXqlOnm/QoEE5AHrTTTelIUOG5AWHPvzwwxyMnGOOOVo9fQxhjxQLIw0ePLjV+ck5EMPgIwAaAdgIgMb8n5EMf58cVWUJECBAgAABAgQIECBAgAABAl1TwBygXbPdWz11DDWP3pxvvPFGXrSoCDoW84O2LFDM7/nQQw/lFdtbno/g6R577JH23HPPdP/997c8PdH9mG+0X79+acyYMWnkyJFp9OjRadlll83HJlrQSQIECBAgQIAAAQIECBAgQIAAAQItBARAW4B05d0i2HnNNdeke++9N8U8nbEqe6MUwdIVV1wxvf/+++mEE05IH330UbNsZ555Zho1alQOYi611FLNzrVnp1gM6de//nXOvtlmm7WnmDwECBAgQIAAAQIECBAgQIAAAQIEmgkIgDbj6No76623XurRo0e6+uqr0yeffJJiWHyjldoLpQMOOCDNPvvsebj8Lrvskk499dQUgc/vf//76bLLLstlDzrooLyoUVGmve8x3+d0002XYrGlmId0o402am9R+QgQIECAAAECBAgQIECAAAECBAjUBARAaxQ2YgGijTfeOE2YMCEHH4temG3JxDD4WDgpAqcvv/xyuuiii9L555+fYjX5/v37p+OPPz5tsMEGbRWf6PF55pknrbHGGjnP2muvnXr27DnR/E4SIECAAAECBAgQIECAAAECBAgQaCTQrSnYNaHRCccIdETg008/TWPHjs1D4vv06ZMigDm56ZBDDsm9S2OIfREMndxrKk+AAAECBAgQIECAAAECBAgQINC1BKwC37Xae6o97QwzzJAWWWSRKXb9t956K40YMSLNO++8abXVVpti13UhAgQIECBAgAABAgQIECBAgACBriUgANq12rvSTxsLKr377rtp3Lhx6bTTTkvRq3T77bfPw/HbW/Ff/vKX6YILLmiYfa211kpnn312w3MOEiBAYGICMR9xzE3cVho2bFhaYokl2jrtOAECBNoU2GeffdItt9zS8Px2222XjjrqqIbnHCRAgAABAgQIEGi/gDlA228l51QWiHlEBw8enHbbbbd03333pQEDBqQdd9yxQ3f9/PPP02effdbw9fjjj6f9998/vf766x26pswECBAIgbY+W+L4sccemy699FJQBAgQ6LDAxP7vcvfdd+f/u8TilBIBAgQIECBAgEB5AT1Ay9spOYUF5p9//rT00kun9957Lw0cODD98Ic/zCvAd+Q2c889d+rbt2+rIhFcHT16dB5WP2TIkNSrV69WeRwgQIBAWwIxzUejz5YPP/wwvfjii+m8887Ln1c77LBDW5dwnAABAg0Fevfu3fDzJeZWf/jhh3Pv0KOPPrrD/ydqeDMHCRAgQIAAAQJdVMAiSF204bvaY2+11Vbp6quvzo/99NNPG6ra1X4APC+BqSQwfPjwtP766+er77XXXumMM86YSndyWQIEuprAyiuvnB544IH82DE9UPfu3bsageclQIAAAQIECEwxAUPgpxilCxEgQIAAAQIECBAgQIAAAQIECBAgUDUBAdCqtYj6ECBAgAABAgQIECBAgAABAgQIECAwxQQEQKcYZfUvFKsU77777unCCy9sVtl99903H3/jjTdqxxsdq52cQhtRl3iNHz9+Cl3RZQgQIECAAAECBAgQIECAAAECBAg0F7AIUnOPTr0Xq58/+eSTeXX1+gd96qmnchDy008/rR1udKx2cgptRF0ixQrKEgECBAgQIECAAAECBAgQIECAAIGpISAAOjVUp7FrbrPNNunjjz82uf401m6qS4AAAQIECBAgQIAAAQIECBAgMGkBAdBJG3X6HHvvvXenf0YPSIAAAQIECBAgQIAAAQIECBAg0DUFBEC7Zrs3e+rnnnsuff7556lv375phhkm/iMRw9Wff/75XL5nz56pV69eza4V13nhhRfSM888k4e29+/fPy288MJp+umnb5av5U79dduqR1w76hpp0UUXbXkJ+wQIECBAgAABAgQIECBAgAABAgRaCUw82tUquwOdUWCPPfbIc4Beeumlab755mvzESMAedRRR6WbbropLbDAAumUU05plnfMmDHpyCOPTKNHj252PIKVhx12WFpiiSWaHa/fmW666dJBBx2UXnrppXTEEUekDTfcsP503r733nvTj3/847TccsulM888s9V5BwgQIECAAAECBAgQIECAAAECBAi0FLAKfEsR+w0FIvh5zDHH5OBn9NA89dRTmwVLR40alVd0j+DneuutlwOehx9+eNpss81SBEYjyFosetToBt26dUubb755PnXDDTc0ypKuu+66fLzI1zCTgwQIECBAgAABAgQIECBAgAABAgTqBARA6zBsNhaYMGFCOvbYY9P111+fFllkkRz87N27dy1znD/ppJPyQkq77bZb7iW68cYbp4022igdcsghaciQIemTTz7JeWqFGmxEYDMCoffcc096++23m+UYP358uv3229NMM83UsHdos8x2CBAgQIAAAQIECBAgQIAAAQIECPxXQADUj8JEBaLn53HHHZeuvfbaPIT9t7/9bZp77rmblXnggQfS448/nucD3WmnnZqdi52tt946By4fffTR9Nhjj7U6XxyI4fcDBw7Mc4fecsstxeH8fuutt+YA6zrrrJN69OjR7JwdAgQIECBAgAABAgQIECBAgAABAm0JmAO0LRnHs0D07BwxYkTePvDAA9Occ87ZSubZZ5/Nx/r06ZMefvjhVufjQMwDGkPgYxGjmMOzrbTFFlukkSNH5t6m2223XS2b4e81ChsECBAgQIAAAQIECBAgQIAAAQIdEBAA7QBWV8wawc+ZZ545ffTRRyl6f55++umtVnSPVd8jPfLII2no0KETZXrxxRcnen7ddddNs802W+5RGnkXXHDB9Morr6QHH3ww9zBdZZVVJlreSQIECBAgQIAAAQIECBAgQIAAAQL1AgKg9Rq2WwkMGDAgxWJGe+65Zw5KXnjhhem73/1uq3xxYKWVVkprrbVWw3PFwSWXXLLYbPgewdZYAX7YsGG5F2jMKVr0/tx0001bBV8bXsRBAgQIECBAgAABAgQIECBAgAABAv8VEAD1ozBRgUMPPTSv9h7D3w8++OB07rnn5iBnLIZUpFgVPlL37t3T4MGDi8Ol32MYfARAhw8fniIAGvN/RrL6e2lSBQkQIECAAAECBAgQIECAAAECXVbAIkhdtunb9+DTTz99zhiLD62//vp5IaJjjjkmL1RUXCHm94z00EMPtVq9PY5/+OGHaY899si9SO+///44NNEUc4T269cvjRkzJs8HOnr06LTsssvmYxMt6CQBAgQIECBAgAABAgQIECBAgACBFgICoC1A7LYtsN9++6WePXumUaNGpRgKX6QY+r7iiium999/P51wwgl5vtDiXLyfeeaZuUwENJdaaqn6U21uRy/QSL/+9a/z+2abbZbf/UGAAAECBAgQIECAAAECBAgQIECgIwICoB3R6uJ555577rTvvvtmhXPOOSf30CxIDjjggDT77LOn22+/Pe2yyy7p1FNPzYHP73//++myyy5L3bp1SwcddFBe4KgoM7H3mO9zuummS7HA0owzzpg22mijiWV3jgABAgQIECBAgAABAgQIECBAgEBDAQHQhiwOtiUQ83Cuuuqq6ZNPPkn1Q+FjGPyf//zntN5666WXX345XXTRRen8889Pzz77bOrfv386/vjj0wYbbNDWZVsdn2eeedIaa6yRj6+99tq552mrTA4QIECAAAECBAgQIECAAAECBAgQmISARZAmAdSZTseCQvFqma6//vqWh/IK7K0O/vdAMSy95fnoIXrUUUelTz/9NI0dOzYPie/Tp0+KYGajdMcddzQ6XDs2wwz/+fEshsPXTtggQIAAAQIECBAgQIAAAQIECBAg0E4BAdB2QsnWfoEIXNavEt/+kl/kfOutt9KIESPSvPPOm1ZbbbUvTtgiQIAAAQIECBAgQIAAAQIECBAg0AEBAdAOYMk6dQViEaV33303jRs3Lp122mm5J+n222+f5wKdund2dQIECBAgQIAAAQIECBAgQIAAgc4qIADaWVt2GnyumDt01113rdV8wIABaccdd6zt2yBAgAABAgQIECBAgAABAgQIECDQUQEB0I6KyT/VBOaff/609NJLp/feey8NHDgw/fCHP8wrwE+1G7owAQIECBAgQIAAAQIECBAgQIBApxcQAO30TTztPGCPHj3S2WefPe1UWE0JECBAgAABAgQIECBAgAABAgQqLzBd5WuoggQIECBAgAABAgQIECBAgAABAgQIECgpIABaEk4xAgQIECBAgAABAgQIECBAgAABAgSqLyAAWv02UkMCBAgQIECAAAECBAgQIECAAAECBEoKCICWhFOMAAECBAgQIECAAAECBAgQIECAAIHqCwiAVr+N1JAAAQIECBAgQIAAAQIECBAgQIAAgZICAqAl4RQjQIAAAQIECBAgQIAAAQIECBAgQKD6AgKg1W8jNSRAgAABAgQIECBAgAABAgQIECBAoKSAAGhJOMUIECBAgAABAgQIECBAgAABAgQIEKi+gABo9dtIDQkQIECAAAECBAgQIECAAAECBAgQKCkgAFoSTjECBAgQIECAAAECBAgQIECAAAECBKovIABa/TZSQwIECBAgQIAAAQIECBAgQIAAAQIESgoIgJaEU4wAAQIECBAgQIAAAQIECBAgQIAAgeoLCIBWv43UkAABAgQIECBAgAABAgQIECBAgACBkgICoCXhFCNAgAABAgQIECBAgAABAgQIECBAoPoCAqDVbyM1JECAAAECBAgQIECAAAECBAgQIECgpIAAaEk4xQgQIECAAAECBAgQIECAAAECBAgQqL6AAGj120gNCRAgQIAAAQIECBAgQIAAAQIECBAoKSAAWhJOMQIECBAgQIAAAQIECBAgQIAAAQIEqi8gAFr9NlJDAgQIECBAgAABAgQIECBAgAABAgRKCgiAloRTjAABAgQIECBAgAABAgQIECBAgACB6gsIgFa/jdSQAAECBAgQIECAAAECBAgQIECAAIGSAgKgJeEUI0CAAAECBAgQIECAAAECBAgQIECg+gICoNVvIzUkQIAAAQIECBAgQIAAAQIECBAgQKCkgABoSTjFCBAgQIAAAQIECBAgQIAAAQIECBCovoAAaPXbSA0JECBAgAABAgQIECBAgAABAgQIECgpIABaEk4xAgQIECBAgAABAgQIECBAgAABAgSqLyAAWv02UkMCBAgQIECAAAECBAgQIECAAAECBEoKCICWhFOMAAECBAgQIECAAAECBAgQIECAAIHqCwiAVr+N1JAAAQIECBAgQIAAAQIECBAgQIAAgZICAqAl4RQjQIAAAQIECBAgQIAAAQIECBAgQKD6AgKg1W8jNSRAgAABAgQIECBAgAABAgQIECBAoKSAAGhJOMUIECBAgAABAgQIECBAgAABAgQIEKi+gABo9dtIDQkQIECAAAECBAgQIECAAAECBAgQKCkgAFoSTjECBAgQIECAAAECBAgQIECAAAECBKovIABa/TZSQwIECBAgQIAAAQIECBAgQIAAAQIESgoIgJaEU4wAAQIECBAgQIAAAQIECBAgQIAAgeoLCIBWv43UkAABAgQIECBAgAABAgQIECBAgACBkgICoCXhFCNAgAABAgQIECBAgAABAgQIECBAoPoCAqDVbyM1JECAAAECBAgQIECAAAECBAgQIECgpIAAaEk4xQgQIECAAAECBAgQIECAAAECBAgQqL6AAGj120gNCRAgQIAAAQIECBAgQIAAAQIECBAoKSAAWhJOMQIECBAgQIAAAQIECBAgQIAAAQIEqi8gAFr9NlJDAgQIECBAgAABAgQIECBAgAABAgRKCgiAloRTjAABAgQIECBAgAABAgQIECBAgACB6gsIgFa/jdSQAAECBAgQIECAAAECBAgQIECAAIGSAgKgJeEUI0CAAAECBAgQIECAAAECBAgQIECg+gICoNVvIzUkQIAAAQIECBAgQIAAAQIECBAgQKCkgABoSTjFCBAgQIAAAQIECBAgQIAAAQIECBCovoAAaPXbSA0JECBAgAABAgQIECBAgAABAgQIECgpIABaEk4xAgQIECBAgAABAgQIECBAgAABAgSqLyAAWv02UkMCBAgQIECAAAECBAgQIECAAAECBEoKCICWhFOMAAECBAgQIECAAAECBAgQIECAAIHqCwiAVr+N1JAAAQIECBAgQIAAAQIECBAgQIAAgZICAqAl4RQjQIAAAQIECBAgQIAAAQIECBAgQKD6AgKg1W8jNSRAgAABAgQIECBAgAABAgQIECBAoKSAAGhJOMUIECBAgAABAgQIECBAgAABAgQIEKi+gABo9dtIDQkQIECAAAECBAgQIECAAAECBAgQKCkgAFoSTjECBAgQIECAAAECBAgQIECAAAECBKovIABa/TZSQwIECBAgQIAAAQIECBAgQIAAAQIESgoIgJaEU4wAAQIECBAgQIAAAQIECBAgQIAAgeoLCIBWv43UkAABAgQIECBAgAABAgQIECBAgACBkgICoCXhFCNAgAABAgQIECBAgAABAgQIECBAoPoCAqDVbyM1JECAAAECBAgQIECAAAECBAgQIECgpIAAaEk4xQgQIECAAAECBAgQIECAAAECBAgQqL6AAGj120gNCRAgQIAAAQIECBAgQIAAAQIECBAoKSAAWhJOMQIECBAgQIAAAQIECBAgQIAAAQIEqi8gAFr9NlJDAgQIECBAgAABAgQIECBAgAABAgRKCgiAloRTjAABAgQIECBAgAABAgQIECBAgACB6gsIgFa/jdSQAAECBAgQIECAAAECBAgQIECAAIGSAgKgJeEUI0CAAAECBAgQIECAAAECBAgQIECg+gICoNVvIzUkQIAAAQIECBAgQIAAAQIECBAgQKCkgABoSTjFCBAgQIAAAQIECBAgQIAAAQIECBCovoAAaPXbSA0JECBAgAABAgQIECBAgAABAgQIECgpIABaEk4xAgQIECBAgAABAgQIECBAgAABAgSqLyAAWv02UkMCBAgQIECAAAECBAgQIECAAAECBEoKCICWhFOMAAECBAgQIECAAAECBAgQIECAAIHqCwiAVr+N1JAAAQIECBAgQIAAAQIECBAgQIAAgZICAqAl4RQjQIAAAQIECBAgQIAAAQIECBAgQKD6AgKg1W8jNSRAgAABAgQIECBAgAABAgQIECBAoKSAAGhJOMUIECBAgAABAgQIECBAgAABAgQIEKi+gABo9dtIDQkQIECAAAECBAgQIECAAAECBAgQKCkgAFoSTjECBAgQIECAAAECBAgQIECAAAECBKovIABa/TZSQwIECBAgQIAAAQIECBAgQIAAAQIESgoIgJaEU4wAAQIECBAgQIAAAQIECBAgQIAAgeoLCIBWv43UkAABAgQIECBAgAABAgQIECBAgACBkgICoCXhFCNAgAABAgQIECBAgAABAgQIECBAoPoCAqDVbyM1JECAAAECBAgQIECAAAECBAgQIECgpIAAaEk4xQgQIECAAAECBAgQIECAAAECBAgQqL6AAGj120gNCRAgQIAAAQIECBAgQIAAAQIECBAoKSAAWhJOMQIECBAgQIAAAQIECBAgQIAAAQIEqi8gAFr9NlJDAgQIECBAgAABAgQIECBAgAABAgRKCgiAloRTjAABAgQIECBAgAABAgQIECBAgACB6gsIgFa/jdSQAAECBAgQIECAAAECBAgQIECAAIGSAgKgJeEUI0CAAAECBAgQIECAAAECBAgQIECg+gICoNVvIzUkQIAAAQIECBAgQIAAAQIECBAgQKCkgABoSTjFCBAgQIAAAQIECBAgQIAAAQIECBCovoAAaPXbSA0JECBAgAABAgQIECBAgAABAgQIECgpIABaEk4xAgQIECBAgAABAgQIECBAgAABAgSqLyAAWv02UkMCBAgQIECAAAECBAgQIECAAAECBEoKCICWhFOMAAECBAgQIECAAAECBAgQIECAAIHqCwiAVr+N1JAAAQIECBAgQIAAAQIECBAgQIAAgZICAqAl4RQjQIAAAQIECBAgQIAAAQIECBAgQKD6AgKg1W8jNSRAgAABAgQIECBAgAABAgQIECBAoKSAAGhJOMUIECBAgAABAgQIECBAgAABAgQIEKi+gABo9dtIDQkQIECAAAECBAgQIECAAAECBAgQKCkgAFoSTjECBAgQIECAAAECBAgQIECAAAECBKovIABa/TZSQwIECBAgQIAAAQIECBAgQIAAAQIESgoIgJaEU4wAAQIECBAgQIAAAQIECBAgQIAAgeoLCIBWv43UkAABAgQIECBAgAABAgQIECBAgACBkgICoCXhFCNAgAABAgQIECBAgAABAgQIECBAoPoCAqDVbyM1JECAAAECBAgQIECAAAECBAgQIECgpIAAaEk4xQgQIECAAAECBAgQIECAAAECBAgQqL6AAGj120gNCRAgQIAAAQIECBAgQIAAAQIECBAoKSAAWhJOMQIECBAgQIAAAQIECBAgQIAAAQIEqi8gAFr9NlJDAgQIECBAgAABAgQIECBAgAABAgRKCgiAloRTjAABAgQIECBAgAABAgQIECBAgACB6gsIgFa/jdSQAAECBAgQIECAAAECBAgQIECAAIGSAgKgJeEUI0CAAAECBAgQIECAAAECBAgQIECg+gICoNVvIzUkQIAAAQIECBAgQIAAAQIECBAgQKCkgABoSTjFCBAgQIAAAQIECBAgQIAAAQIECBCovoAAaPXbSA0JECBAgAABAgQIECBAgAABAgQIECgpIABaEk4xAgQIECBAgAABAgQIECBAgAABAgSqLyAAWv02UkMCBAgQIECAAAECBAgQIECAAAECBEoKCICWhFOMAAECBAgQIECAAAECBAgQIECAAIHqCwiAVr+N1JAAAQIECBAgQIAAAQIECBAgQIAAgZICAqAl4RQjQIAAAQIECBAgQIAAAQIECBAgQKD6AgKg1W8jNSRAgAABAgQIECBAgAABAgQIECBAoKSAAGhJOMUIECBAgAABAgQIECBAgAABAgQIEKi+gABo9dtIDQkQIECAAAECBAgQIECAAAECBAgQKCkgAFoSTjECBAgQIECAAAECBAgQIECAAAECBKovIABa/TZSQwIECBAgQIAAAQIECBAgQIAAAQIESgoIgJaEU4wAAQIECBAgQIAAAQIECBAgQIAAgeoLCIBWv43UkAABAgQIECBAgAABAgQIECBAgACBkgICoCXhFCNAgAABAgQIECBAgAABAgQIECBAoPoCAqDVbyM1JECAAAECBAgQIECAAAECBAgQIECgpIAAaEk4xQgQIECAAAECBAgQIECAAAECBAgQqL6AAGj120gNCRAgQIAAAQIECBAgQIAAAQIECBAoKSAAWhJOMQIECBAgQIAAAQIECBAgQIAAAQIEqi8gAFr9NlJDAgQIECBAgAABAgQIECBAgAABAgRKCgiAloRTjAABAgQIECBAgAABAgQIECBAgACB6gsIgFa/jdSQAAECBAgQIECAAAECBAgQIECAAIGSAgKgJeEUI0CAAAECBAgQIECAAAECBAgQIECg+gICoNVvIzUkQIAAAQIECBAgQIAAAQIECBAgQKCkgABoSTjFCBAgQIAAAQIECBAgQIAAAQIECBCovoAAaPXbSA0JECBAgAABAgQIECBAgAABAgQIECgpIABaEk4xAgQIECBAgAABAgQIECBAgAABAgSqLyAAWv02UkMCBAgQIECAAAECBAgQIECAAAECBEoKCICWhFOMAAECBAgQIECAAAECBAgQIECAAIHqCwiAVr+N1JAAAQIECBAgQIAAAQIECBAgQIAAgZICAqAl4RQjQIAAAQIECBAgQIAAAQIECBAgQKD6AgKg1W8jNSRAgAABAgQIECBAgAABAgQIECBAoKSAAGhJOMUIECBAgAABAgQIECBAgAABAgQIEKi+gABo9dtIDQkQIECAAAECBAgQIECAAAECBAgQKCkgAFoSTjECBAgQIECAAAECBAgQIECAAAECBKovIABa/TZSQwIECBAgQIAAAQIECBAgQIAAAQIESgoIgJaEU4wAAQIECBAgQIAAAQIECBAgQIAAgeoLCIBWv43UkAABAgQIECBAgAABAgQIECBAgACBkgICoCXhFCNAgAABAgQIECBAgAABAgQIECBAoPoCAqDVbyM1JECAAAECBAgQIECAAAECBAgQIECgpIAAaEk4xQgQIECAAAECBAgQIECAAAECBAgQqL6AAGj120gNCRAgQIAAAQIECBAgQIAAAQIECBAoKSAAWhJOMQIECBAgQIAAAQIECBAgQIAAAQIEqi8gAFr9NlJDAgQIECBAgAABAgQIECBAgAABAgRKCgiAloRTjAABAgQIECBAgAABAgQIECBAgACB6gsIgFa/jdSQAAECBAgQIECAAAECBAgQIECAAIGSAgKgJeEUI0CAAAECBAgQIECAAAECBAgQIECg+gICoNVvIzUkQIAAAQIECBAgQIAAAQIECBAgQKCkgABoSTjFCBAgQIAAAQIECBAgQIAAAQIECBCovoAAaPXbSA0JECBAgAABAgQIECBAgAABAgQIECgpIABaEk4xAgQIECBAgAABAgQIECBAgAABAgSqLyAAWv02UkMCBAgQIECAAAECBAgQIECAAAECBEoKCICWhFOMAAECBAgQIECAAAECBAgQIECAAIHqCwiAVr+N1JAAAQIECBAgQIAAAQIECBAgQIAAgZICAqAl4RQjQIAAAQIECBAgQIAAAQIECBAgQKD6AgKg1W8jNSRAgAABAgQIECBAgAABAgQIECBAoKSAAGhJOMUIECBAgAABAgQIECBAgAABAgQIEKi+gABo9dtIDQkQIECAAAECBAgQIECAAAECBAgQKCkgAFoSTjECBAgQIECAAAECBAgQIECAAAECBKovIABa/TZSQwIECBAgQIAAAQIECBAgQIAAAQIESgoIgJaEU4wAAQIECBAgQIAAAQIECBAgQIAAgeoLCIBWv43UkAABAgQIECBAgAABAgQIECBAgACBkgICoCXhFCNAgAABAgQIECBAgAABAgQIECBAoPoCAqDVbyM1JECAAAECBAgQIECAAAECBAgQIECgpIAAaEk4xQgQIECAAAECBAgQIECAAAECBAgQqL6AAGj120gNCRAgQIAAAQIECBAgQIAAAQIECBAoKSAAWhJOMQIECBAgQIAAAQIECBAgQIAAAQIEqi8gAFr9NlJDAgQIECBAgAABAgQIECBAgAABAgRKCgiAloRTjAABAgQIECBAgAABAgQIECBAgACB6gsIgFa/jdSQAAECBAgQIECAAAECBAgQIECAAIGSAgKgJeEUI0CAAAECBAgQIECAAAECBAgQIECg+gICoNVvIzUkQIAAAQIECBAgQIAAAQIECBAgQKCkgABoSTjFCBAgQIAAAQIECBAgQIAAAQIECBCovoAAaPXbSA0JECBAgAABAgQIECBAgAABAgQIECgpIABaEk4xAgQIECBAgAABAgQIECBAgAABAgSqLyAAWv02UkMCBAgQIECAAAECBAgQIECAAAECBEoKCICWhFOMAAECBAgQIECAAAECBAgQIECAAIHqCwiAVr+N1JAAAQIECBAgQIAAAQIECBAgQIAAgZICAqAl4RQjQIAAAQIECBAgQIAAAQIECBAgQKD6AgKg1W8jNSRAgAABAgQIECBAgAABAgQIECBAoKSAAGhJOMUIECBAgAABAgQIECBAgAABAgQIEKi+gABo9dtIDQkQIECAAAECBAgQIECAAAECBAgQKCkgAFoSTjECBAgQIECAAAECBAgQIECAAAECBKovIABa/TZSQwIECBAgQIAAAQIECBAgQIAAAQIESgoIgJaEU4wAAQIECBAgQIAAAQIECBAgQIAAgeoLCIBWv43UkAABAgQIECBAgAABAgQIECBAgACBkgICoCXhFCNAgAABAgQIECBAgAABAgQIECBAoPoCAqDVbyM1JECAAAECBAgQIECAAAECBAgQIECgpIAAaEk4xQgQIECAAAECBAgQIECAAAECBAgQqL6AAGj120gNCRAgQIAAAQIECBAgQIAAAQIECBAoKTBDyXKKESBAgAABAgQIECBAIL39TkoffNgYYrpuKc03b+NzjhIgQIAAAQIEviwBAdAvS9p9CBAgQIAAAQIECHRCgZ8cmdIFlzd+sFlnSem1Jxqfc5QAAQIECBAg8GUJGAL/ZUm7DwECBAgQIECAAAECBAgQIECAAAECX7qAHqBtkH/++efp008/TTPNNFMbORwmQIAAAQIECBAgQGCZ/imt+/WUh8I//Ph/PPrMl1L/xVKaeWY+BAgQIECAAIGvXkAAtK4Nnn/++XTRRRelp59+Ov3rX//KAdC+ffumJZZYIq1tlCFUAABAAElEQVS55ppp4403rsttc8iQIemjjz5KJ5xwQpprrrmmOsgLL7yQoj0kAgQIECBAgACB6ggc8L8pxeu2ESkN+s5/6jWo6b/NJx1VnTpWqSbvvpfSx580rtH006c01xyNzzlKgAABAgQIlBcQAP2v3V133ZV+8YtfpPHjx+cjs846a+rZs2d69tln8+umm25KDz74YNpvv/3SjDPOWF68E5WMQPEHH3yQA8VT87E+++yzdPbZZ6fLL7883XDDDVPzVq5NgAABAgQIECBAYKoK7LRPSjfd1vgWCy+U0uN3Nj7nKAECBAgQIFBeQAC0yW706NHpoIMOyorf/e5307e+9a0099xz5/3o4XjzzTen008/PQ0bNix98skn6eCDDy4vrmSHBd5///10/vnnpxlm8OPaYTwFCBAgQIAAAQIECBAgQIAAAQJdXMAiSE0/AHfe+Z+vWbfccsu011571YKf8bMxc9PERVtssUU64ogjYjcNHz48ffzxx3nbHwQIECBAgAABAgQIEOiIwLJLprTGwJSWWPSLUgv1+c+xlQd8ccwWAQIECBAgMOUEdKlrsoyh7ZEWW6xppvY20iqrrJL69OmT/v3vf6eHH344xX7L9Prrr6dnnnkmvfrqq2nBBRdMiy++eJpzzjlbZkvvvPNOevPNN1OvXr3yMPvo4fjQQw/lwOqKK67YbD7NCLY+9thjaezYsWmhhRZKX/va19J00zWOW8fCTTFPZtQhho33798/Lbzwwmn6mEyoLsVcp3F+gQUWyAHeulMpnuG9995Ls88+e5pnnnnqT+Xh7i+//HKK6QHmn3/+ZufiemPGjElPPfVUfq7lllsuzTbbbM3ytNyJez333HPpxRdfzPeL5+vXr1+zKQYiz0svvZSLTpgwId8jdiJfWw4t72OfAAECBAgQIECAQFUEjjnkPzW5ZFhKuw79z/ZOg1M6eL+q1FA9CBAgQIBA5xMQAG1q06WWWiqNHDkyXX311Wm77bZrFTAsmv2Pf/xjmmWWWVoF3iJgGHNUXnnllSmCkEWKAN23v/3t9IMf/KDZavLXXnttOu2009JPf/rTHCw977zzmpWLOuy///7pH//4RzrssMNy4LG45jLLLJOOO+64ZkHSOBfBxyOPPDIP5y/yxvuiiy6arxELORXppJNOSvfee28e9j9o0KDicH6Pnq4RjF199dXTiSee2OzcVVddlX7729+mwYMHp332aZq86L8pApg/+9nP8uJRxbFu3bqlXXfdNb+KY8V7BIjjGf75z38Wh2rvEZT9+c9/niIQHOlPf/pTuuKKK/J2BFl32mmnvH399den7t27521/ECBAgAABAgQIECBAgAABAgQIEGhLQAC0SWbddddNF154YV75PQJs3/zmN9Nqq62We0/WwzUKuEWvxEMPPTTdf//9ucfkjjvumFcqj8WTLrnkkvTXv/41Pf744+mUU05JERSsTxdccEHu/bjeeuulFVZYId1zzz35FYv9fPrpp+maa65JX//613NdXnnllfS3v/0tjRo1Kv3+979PP/nJT2qXimMRkIzeonGteMW94nrXXXdd2mOPPdIZZ5yRA71RaO21184B0AhA1gdAYwGoRx99NF83gqBRh/p5N0eMaFrasymts846+b3448ADD8w9XePZo5fsrbfemh555JF07rnn5ukEttlmmyJr7l26yy675PcIcoZz9JYNv7h+9PYMz8suuyz3Tl1//fVT7969c4A5AspF4HWmmWaqXdMGAQIECBAgQIAAAQIECBAgQIAAgbYEBECbZJZddtl0/PHH58BbDA8/+eSTs9d8882XVlpppTRw4MC01lpr5eHqLSEjUBfBu+i5eOaZZ9Z6ZkZQdfPNN8/BxxhiH8HM+mBjXCeGq++9997pf/7nf/Jld9hhh3Tsscemv//973nBpViQKeYkLdKSSy6Ze3NGz9AiRQA2enRG8HO33XZr1uNyo402ysPwo7dp5IkgaKR4lt/85je512v0WC2Gkj/wwAN5aHwEFz/88MMcuI3AbKRx48blqQJiSP/yyy+fjxV/xLGzzjorD32PYxEI/d3vfpf+/Oc/5+euD4DGs0WP2ZhuIOpUDM/fYIMN8rQA2267bZ4iIIK3YbjyyivnZ4getlHPuLZEgAABAgQIECBAgAABAgQIECBAoL0CjSeTbG/pTpQveiJGj8UIQs4777z5yaLXZfSgPProo9PWW2+dz0fAsT7FsPdIu+++ey34WZyPnosRlIwUPUxbpphjswh+FueKod+xXwz3Ls7FvJqRXnvttdw7M7YjaBk9TGM+0Zb543zUOwKa0bMz5hKNFIHdmB/03XffTU888UQ+Fn/EsPhIsRhUpAjsFil6i8YQ9DXXXLMWtCzORY/OuH99il6okWLO0PoUQ/F/+MMf5uH/RfCzOD/33HPXgqsRJJUIECBAgAABAgQIECBAgAABAgQITK6AHqB1grEIz49+9KP8isV57rvvvhwEjODfBx98kP7whz+kJ598Mh1++OF5/skYIh69OCNFALVRKo7HIkYRQKwP+kWv0ZYp6hApgqMth9xHgDBSBGHjWjE8PYbaR4qh57E4U6MU84BGveOZiiBqDIN/+umnc9AzesBGigBo9OaMXpgxDD+eP4KbkYrh79Ers2WKBYlapqKuMay+PsXiUfULSMVzxMJS0fM2ArTFgkdxXCJAgAABAgQIECBAgAABAgQIECAwuQICoG0IRlAvXrEg0UcffZRioaLzzz8/BwJjAZ6YJzSCdRGoi1XR55hjjoZXil6gEfSMYGn0KK0PekbQsmUq5gnt0aNHy1Ot5hCNDEUANubcHDr0v8tItir5nwOxWFGRYhh8BHRjqPnOO++c6xZByBiKHgHTueaaKwck49lnnHHGvCBTLABVH7wsrhU9Slum4jla9piNfNEr9OKLL84B1rhn2BSpPkBcHPNOgAABAgQIECBAgAABAgQIECBAoKxAlw+A/utf/0p33nlnioBjBDsbpZlnnjkP245gZwRB77777hwALRYIiuMR6CuCfvXXiHPxitQyuNdoIZ9GAcP667W1HXOVRlBzYinmEC1SrHwfwdkYPh/ze44cOTKfKgKcMe/pTTfdlBczigDv22+/nefkDIuWqZhDtOXxRvvRE3XffffNPWrDL+qx9NJL53k+Y77PWGX+rrvualTUMQIECBAgQIAAAQIECBAgQIAAAQIdFujyAdAYfh0L7EQwcrPNNms17LxedMCAAXk3ykSKno8R1IwFiN588808bD2fqPsjen0WKYaXT+nUt2/ffMkYLj948OAOXT6GwcfK8jHUvQiARuAzUgRCIwAa54oAZ8vV3zt0s/9mPuaYY3LwMxZoOuigg/JK7/XXKWxjcSaJAAECBAgQIECAAAECBAgQIECAwOQKdPlFkGJOzAh+RhAzVnSfWIq5QCOtvvrq+T2Cn4ssskjevvnmm/N7yz+K48sss0yrYF/LvGX2Y7h6pIceeij30mx5jVjNfY899kh77rlns0WNIl/RYzSeKxZTiuH5xRD9oidoBECjR2Y8ayyANDkpFl2KHreRfvCDH7TyiHlWiyH9Ra/ZyFsEYMv2jo1rSAQIECBAgAABAgQIECBAgAABAl1ToMsHQKNX5o477phb/3e/+136v//7vzwfZv2PQwQRTzvttLwwUBwvVjiP7WKV9z//+c/pmWeeiUO1FCusX3DBBXk/VpefGimGvsfK8e+//3464YQT8nyl9fc588wz06hRo9KYMWPycPP6czHkPIa333jjjemNN95IRe/PyBO9W6N3aTzD6NGj09e+9rU0++yz1xfv8HYMny+mAahfYT4uFHONRo/QTz75JF83AtJFKobdR1D0tddeKw57J0CAAAECBAgQIECAAAECBAgQIDBJgS4/BD6E9tprr9SzZ8901llnpWuuuSa/YlGj6N35+uuv58WOovdh9BQ95JBDUjEUPsrGqujrr79+uvXWW3Mvyw033DAHDmPF9ej9GQv8xOJEm2yySWSfKumAAw5I++yzT7r99tvTLk2rtkfPzphfM3puPtu0SnzMTRrBxdlmm63Z/WNxozXWWCPXPU7UB0BjP3qBFj0yp8Tw9whkxiJLEXCNgPKDDz6YVlhhhRxgjRXoX3311RykjXlC6wOd4T7PPPPkIG0EnCM4e+yxx6ZevXpFNSUCBAgQIECAAAECBAgQIECAAAECbQoIgP6X5rvf/W4OeF566aW5t2T0iIxh5ZEiGBqL9fzwhz/MC/b8t0jt7Re/+EW64oor0jnnnJOuvfbafDwCkDHsfdCgQflVyzwVNmIYfPRA/fWvf52DnhdddFHtLv37989D4CPQ2ShFsDSCt5GiR2h9igBozBEaaUoEQOM6Bx54YF5VPpwiEBqv6BUawdfowfrWW2+lIUOGpDvuuCMvllQsLHXooYemo446KgdBY0GmCOwKgIaoRIAAAQIECBAgQIAAAQIECBAgMDGBbk09GydMLENXPffOO++k6MUZK6X36dOn3QzRYzQWPlp88cXTLLPM0u5yUypj9DgdO3ZsHhIf9Y6ek1VM7733XnrxxRdz8LNfv365d2176hmB6QguR1C6I2mrrbZKV199dS7y9NNPpyWWWKIjxeUlQIBAQ4Hhw4fnUQBxMkYTnHHGGQ3zOUiAAIGOCsQX0zFHe6Rx48ZNdKHOjl57auW/bURKg77zn6vv/r2UTjpqat2pc1z3kmEp7Tr0P89y8H4pxUsiQIAAAQIEpo6AHqBtuEaALYZndzRFr8SvsmdiBAdj6H7VU0w5sPTSS3e4mlUN6Hb4QRQgQIAAAQIECBAgQIAAAQIECBD4UgQEQL8UZjf5sgRiwafnn3++1e2ix2n0yI0FrSQCBAh0VGD8+PF5ao6W5R577LHUo0eP3Dur5Tn7BAgQaI9A9PKMedBbphjVE/Onx0KREgECBL5MgSuvvDJtu+22k3XLSy65JE2thYAnq2KTKDxixIi05pprTiJX89Pxu2axYPDPf/7zdMwxxzTPYI8AgUoICIBWohlUYkoJXHzxxemvf/1rw8tF79EYdi8RIECgowIx/UYsaNcoLbDAAnle4kbnHCNAgMCkBM4+++y8cGajfHPOOWeeWqnROccIECBAYMoJxDR2P/7xj1OsCfLBBx9MuQu7EgEClREQAK1MU6gIAQIECBAgQIAAAQIECBD4agViMd+jjz66YSXuvffevABwnPzmN7+ZYuHcRmn55ZdvdLiyx4444oj0l7/8Jfe872glY+HeYv2PmJJOIkCgmgL+dlazXdSqpECsVh/zi7ZMMQTj5ZdfbnnYPgECBNolEMOa9txzz1Z5Y8qN+M/yZ5991uqcAwQIEGiPwGabbdZwccZzzz3X9BrtAZSHAIEpLrDkkkumgw8+uOF1f//739cCoFtuuWXabbfdGubrSgdjOiS9RrtSi3vWaVVAAHRabTn1biiwwQYbpHi1TLfeemt69913Wx62T4AAgXYJxMJ4BxxwQKu8sQr8ySef3Oq4AwQIEGivwNZbb90wa3y58v777zc85yABAgQIECBAgEDHBARAO+YlNwECBAgQIECAAAECBAgQINAOgU8++STFYm+Rll122dS9e/cUCw3dcsstqU+fPmm77bZLsVbDxx9/nB588MGcb+GFF07zzz9/3m75R8zLPnr06Hx4ueWWS7PNNlvLLOnpp59O//znP3O+GJoe943XoosummK4en166aWX0tixY2uL0U2YMCGXjTxRh6jLpNLnn3+eRo4cmbPF3PALLbRQrUiMFoqRiDGaaOmll87HY+G7u+++Oz9vv3790sorr5xiyoDpppuuVq69GzEK6b777svZY+qCGA0Zi+g9/PDD+R7RCSiuP3DgwNSrV69JXjaeP/weeuihFIt9xvOsuOKKacCAAWnWWWdtVv71119P//rXv/KxpZZaKkWHgZYpFoiKhYojtdWuUd/7778/51lkkUXSvPPOm7eLPzrSnkUZ7wQaCjT9gEsEOr1A0/CMCU1/AfKr6QO00z+vByRA4MsRaOpdXvts2Wuvvb6cm7oLAQJdQmCllVaqfb6MGzdumnjm4XdNmDBbv/+8fnTINFHlr7SSF1/5hdfRv/lKq+LmBNot0LRwW+2z6ZxzzplkuX//+9+1/HfdddeEb3/727X9+P2sKTA4oam3+4Rnn322dvyEE05o87p/+tOfavmagpzN8jUF5CY09aqf0BTkrOUpfgeM9w033HDCCy+80KzMUUcd1TBv5N9vv/2a5W1rpynIWLtG0yrwzbL96Ec/yufWW2+9CU1B3gnf+973annr67b22mtPaArENivbnp233nqrdr34f+mdd945oSmgXDtW3KMpEDzhrLPOmugl4/fk1VdfvVXZuEZTUHLCVVdd1ax8U+C1lvdXv/pVs3PFzumnn17L0zRdQnG42ftNN91UyxP1L1KZ9izKeifQSKDjXzE0/fRL06bAsGHD0u67754uvPDCZg+w77775uPxbVqRGh0rzk2p96hLvMaPHz+lLuk6BAgQIECAAAECBAgQIFBBgabgaavfRddaa62GvTg7Wv0PP/wwbbXVVil+520KfKSmQF7aeeedcw/TomfizTffnFZYYYXUFGytXT56ocZCTr17987Hoodo7Merb9++tXyTu9H0RVbaZptt8tzx0Uvz61//er5H0euzKfCXVl111RTPUTb9/e9/TxtvvHGK3+uXWGKJtNFGG9V6fcZ1Yz77tqZuuvzyy3NPz3vuuSf3kl1ttdXSrrvumq8RvVej12r4/uxnP6tVL3qWFr1db7jhhtrx+o3649Hrt1G6+uqr8+H55psvu8RO2fZsdH3HCBQCAqCFRBd4jy7qTz75ZHrllVeaPe1TTz2Vj0fX8yI1Olacm1LvUZd4WTxkSom6DgECBAgQIECAAAECBKop8Mc//jEPez/jjDPysPiTTjop/fjHP54ilb3yyivzkO+4WFOvw/SPf/wjxf0uu+yyFL8HH3fccfk+TT0m0x/+8IfaPWMRp1jZfvvtt8/HZpppprwfxxrN/14r2MGNGCJ/7bXXpuho9OKLL+ZpAOIeEViMQGKkpt6y6YILLujglb/IfuKJJ6YIIsb6FzFs/MYbb8zXr3/eCIDGkP36FCZ77LFHXngvgr5RPgKhsRhfXCOGuUdgNdLxxx+fmnry1ooX81jffvvtrYK3EV+IaxUpAs9jxowpdmvvRQA0AqxFQLhse9YuaoNAAwEB0AYoXe1QfBMVH/gxH4tEgAABAgQIECBAgAABAgSmhkAEJZumDcq9DZuGhzdcwLbMfe+4445cbO65587BvPprzDDDDDmYGfNUxvyS0dnnq0jf+MY30imnnJLn6SzuH/OfRpC2SNGDdXJSBDvjPkWKHq277LJL7g0bxyIA+cgjjxSn8/thhx2We41G8DFGizYN1292Pup4zTXXpPCLNHTo0FoQtQiAfvDBB6log6JwzMP6zjvv5PlP55xzzny4ZS/QaItnnnkmn9t2222LorVrVbk9a5W1Mc0ICIBOM0019Sq69957p6b5TZp9EE+9u7kyAQIECBAgQIAAAQIECHQ1gQigbbLJJlPlsWMoe6Q333wzXXrppa3uEUHQWNQnRkNOTi/LVhfuwIGf/OQnDXPHwj8xzDzSa6+91jBPew7GEPr64Gd9ma997Wu13fp7xGjMmJog0uabb57WXHPNWr76jfCLwGekWLDo0Ucfzdvrr79+LY5w/fXX52PFH9F7NFIEVNdYY4283TIAWvT+7NGjRx5unzM1/TEttGdRV+/TjoAA6LTTVlOtps8991z+Jqh+CHxbN4sPyPjWKF4xlKBliu70cb2YXyXm+4h87RniXn/dtuoR1y7u3fK+9gkQIECAAAECBAgQIECgugL9+/efapWL4F2RmhZaSjG36P/93//lYF3MCRpp+umnL7J8Je+LLbZYm/eNIGikTz75JL+X+aM91295j1il/qOPPsq3iyBpDIdv67XkkkvWqhVD7CPFlAGbbbZZ3m4ZAC3m/4y5SKM9ItUPiY/9IgAa15h55pnjUE7TQnsWdfU+7QgIgE47bTXVahrzfey000652/vEbhIByKZV8nLegw46qFVgM4KTMYdK08p26Ygjjki//OUvc96YPLno1t7W9aO7fVwz6nHbbbc1zBZzpMT5Yv6WhpkcJECAAAECBAgQIECAAIHKCcTCPFMrxTya0ZMxeipGGjFiRDr44IPTwIED0wILLJAX9LnuuutSW51tpla96q+78MIL1+8225511lnzfsv5OZtlmsROe64fl6i/R/10AMccc0yKIedtvYp5QOMaRQA0toth8NEr9KWXXopDeeh7DIGPtOGGG9Z6psY8p6NGjcrHY3h8MWy+fvh7nJwW2jM/hD+mKQEB0Gmqub66ysaHZHwg3nTTTXk1vFNPPTVPsFzUKD7EYkX30aNH5y7uMY/I4Ycfnr8NisBoBFljwaO2UsxNUnzLU3xT1DJv/IMVqcjX8rx9AgQIECBAgAABAgQIEKimQK9evaZqxeL30eHDh6cdd9wxzTLLLLV7vfzyy3lBpPg9cp111qkF6WoZvqSN+jpNjVuWuf7YsWNLVeWFF16oldtiiy1qgefid/no6RnB5vnnnz8tt9xyafXVV08xzD1SMQw+eoxGnhlnnDENGjSodr1io+rtWdTT+7QjIAA67bTVV1bTGDJw7LHHpviAiq75Efzs3bt3rT5xPlbw+/jjj3MP0OglGt8ORVf3Qw45JA0ZMiR35Y88E0vxD1IEQmPFubfffrtZ1vHjx6dYWS662Mc3SBIBAgQIECBAgAABAgQIdD6B+h6KLZ8uFtuZWIqh1hdffHGeCzQ60Oy///5pmWWWqRWJ1eFjrszJGWpeu1gn2FhooYVqT3Heeeeld999t12vX//617Vy0WN07bXXzvtFALSY/7P43T2CnMXiSkUAtBj+HseLRZJqF/3vhvZsKWJ/cgQEQCdHrwuUjX98Ysj5tddem2LIwm9/+9vcJb7+0R944IH0+OOPp/hGL4aot0zRJT4Cl9ElPiaebivNN998eYhCzAdafCgWeeMbpAiwxjd2xTdHxTnvBAgQIECAAAECBAgQIDDtCsSUaEWaWHDyjTfeKLJN9D2GlG+66aYpAnXxu2r8HrrsssvmMjFMO4bISynVz8saIzZ79uzZrlf9fJ3hWAyDj8BnxBCK3+eLAGjkiQ5SkeJ3+2jjiDFEajn8PR9s8Yf2bAFit5TAF58ypYor1NkFotfm3//+9/yYBx54YMNvZp599tl8PlZqe/jhh1MEROtf8UG66KKL5jyxQNLEUnSfj9RyAmXD3yem5hwBAgQIECBA4KsTiPVFLm/67+Jhx31Rh79dk9Lxv03p3fe+OGaLAAECbQkUc2DG+UaL7Rblinkli/14jw40se7Eaqut1rBDTuSJ4Gf9WhIx6rA+xUjESMWCSfXnOvN2jPAshs7H7/0T6317ySWXpFgoaZtttkl33nlnM5YiABptd80116Qnnngin28UAI1Fls4444zczuEe16tPU6I9669nm0AhIABaSHhvKBDfjBXf7kTvz/gwapmK+T8eeeSRNHTo0IavYv7PF198sWXxZvvrrrtumm222fK3dEXeV155JT344IO5h+kqq6zSLL8dAgQIECBAgACBr04gApzb7pzSTkNSuu+hL+rxxpsp/eJXTQtZNM1cVH/8ixy2CBAg8IXAPPPMUxvpd+GFF7aaEi1yXnbZZemqq676otB/t2J19+iUE4vm/uUvf8m/O7bK1HSgPri55pprNstSBAFj1OH777/f7Fxn3ometz/60Y/yI8bv3BGYbJTCJNb5iA5PMcx96aWXbpZt8cUXz3N9xsGYBi9S9C6tX5hp+eWXz3OCxrlf/OIX8ZZHgNYPw49jU6I94zoSgZYCAqAtRew3ExgwYEA6//zzU/yDFEMH4h+jttJKK62U9tlnn4m+JhXAjGBr8S1R0Qu06P0ZQxjiw1AiQIAAAQIECBD46gWi5+f39k7p5tvbrsvLr6a0TdMMSc9+sV5G25mdIUCgywpET8DvfOc7+flj0aKdd9453XfffTloGaMITzvttPS9730vL5jTCGmXXXbJhyPIuddee9VWGi/yRo/FWJsiUqxn0TIAOtdccxVZ05FHHplXJ4/ff7tCOvTQQ9OCCy6YHzWCoRHAHDduXN7/6KOP8lD1GKlZ9Orce++9c+ekljZFL9AIkkYqfq+vz1ccK6YyaGv4++S2Z/09bRMoBARACwnvDQXiwzDm5ozh75HOPffc/O1afea+ffvm3e7du6fBgwdP9BVB0kmlYhh8rOAXKeYIiWT198zgDwIECBAgQIBAJQQubeqIdcsdk67K2+809Qg6etL55CBAoGsL7LfffrnjTSgMGzYsReeZOeaYI8Uw7ehoM/vss6fLL7+8IVIETIugWQxvj5XHo2fhyiuvnHsdxloSMXIxpm2LXqT1c47GBWMhnmIY/IknnphiZOLPf/7zhvfqbAdjjY3o6BS/18eIz2OOOSZbRy/PWOcjfj+/447/fNhvt9126fjjj29IUARAi5NFsLPYj/diHtDiWFsB0Mltz+L63gnUCwiA1mvYbiVQ9LiMfzDWX3/9vBBRfCDWD4Uv5vd86KGHGg5V+PDDD9Mee+yR9txzz3T//fe3ukfLA/GPVb9+/dKYMWPSyJEj0+jRo/OcLXFMIkCAAAECBAgQqIbAny9ufz2uuiGlN99uf/7OnLNpfZB00RUp/bpupOlfLknprPNSaupsJRHosgKxWnsMw954443TDDPMkB3+P3v3AR9VlfZx/E/vHQHBCkhRQUSkiAqIrG0tqKhrx4avCiq6q2JnXXBddBFRWJBiwy7uin1FRSxLsYAg1YJIkd4xQOY9z4l3MklmkpmQTCbJ73w+Ye4999x7z/1eDObJc87ZsmWLX1DXfh61LE4LaMYqY8aM8UO4LWBqmaA2pZqtTWFTqtkq46effrr/+bJTp045LmEBz5EjR6px48bhY9999114u6Rv2Crutmjx1Vdf7YOfNheoTWMXTAdgP/OPHTtWL774YsxRmebaqFEjT2UBZosfZC+RQVEbIm8/+8cqe/M+Y12T+tItUMZ9Y3CDVyilQcCyNydMmKBzzz03PM+HPbcNLd++fbteeeUVn+0Zq279+vV+2IH9I2TDCi666KIwW//+/f0/VvYPh80NEswbag1sISWbr8Umtp48ebKf49Pq7R8xKzZJsq02F1kmTZrk//Gy30LZb+oGDhyo3r17RzZJaNv+sZsyZYo/Z/HixX5F+4QuQGMEEEAgioBlqgf/c2ffF2PNmxTlVKoQQACBXAXsh3z7wd2KDUW0kTapVg5ol1hQ863npeO7pNpTJLc/a93cqBddK306I/p9WzSVXhonNT84+nFqESgtAjt27PA/X+7evVtHH310eKGeeJ7fgnfLly/XsmXLfIKOBdmCpJ14zl+5cqX/+dgySCN/ro3n3JLSxn4Gnzdvnndv2rSpz6bNnjWbrGfd2/eZrH5yn9QXyPi1Sur3kx6mgEDdunVlgU7LAB03bpyfNyX4h8QClDYsYdq0aX7oQdeuXf1v7T799FM/ZN6GE9x+++3h4Gdej2NB2X/9618++FmhQoUcqfJ5nc9xBBBAAAEEEEAAgcIV2LEzseu7QUGluuzaJfW5UpqZEdeOarHoe+l0l2Mw/U2pXuaUhFHblpbK99xsWOvdNArRSn1ndGK3aEeoK+4CljzTpUv+fmNigTpbfCdyAZ5EPGyYfGkvlogUTHVX1BZ7+z6Luv/cP3UECICmzrsoFj2xeTjff/99v8KeBUJHjx7tU+AtEPrMM8/okUcekQU9LTU+KJbabkPgO3fuHFTl+WmLLll7W4Xe0vGzZ4jmeQEaIIAAAggggAACCBSqwMEHSPMXxX+Lg1z70lzGTco9+BnY/LxCGvJP6eHBQU3p/rxvmDRnXnSDDi4LmQBodBtqEUAAAQSyChAAzepRoveuuOIK2Vf2Eqy2HlkfrS44bkHOaMUyRB944AHZMAUbcmDzhdhvzyyYGa0EEylHO2Z1wbwvwaJIsdpRjwACCCCAAAIIIJB8gdP+EH8A9BA3tLtFs+T3MZXu+FRmfkCe3Zrk1nl58G65Fa/zbEoDBBBAAAEEEIhDgABoHEg0SUzAApc28fTelA0bNvjszwYNGqhjx457cynORQABBBBAAAEEECgEgRvccO5xz8Y3D+h9fy6EDhSjS7r8AH2bwHoqW7ZKS3+UWh1SjB6ykLp6zSXSql+lGW4t1fc+yrjJyT2lDkdIjRsW0k25LAIIIIBAiRMgAFriXmnxfSDLGN28ebOf6P/xxx/3maTnnHOOimqy5eIrSc8RQAABBBBAAIHCF7A5Kp8fI53TV9q6Lfb9/nKDdOYpsY+XhiM73eruiS49m+gcqyXV8fILMp7s8fGZAdCTuktXu8AoBQEEEEAAgXgFCIDGK0W7QhdYtWqV+vZ1/wf9e2nTpo369OkT7PKJAAIIIIAAAgggkGICXd1AnWn/kW5/wAWn3GI1kaXpgdL9t0m9T42sLZ3b1atJdV3AeP2G+J9//ybxt6UlAggggAACCOQuUDb3wxxFIHkCjRo1UqtWrdSkSROdccYZfrV5WwGeggACCCCAAAIIIJC6Aja352sTpGefyOzj2X90C9d8TPAzU0Q6rVfkXu7bnY+S6tfNvQ1HEUAAAQQQQCB+ATJA47eiZSELVK9eXWPHji3ku3B5BBBAAAEEEEAAgcIQqFM786p1I7Yza0v3lk0F8LLLlt25M2+Hu2/Juw0tEEAAAQQQQCB+ATJA47eiJQIIIIAAAggggAACCCCQL4GDD3CLRv3TreyeRwrK3wZJ3Y7J1y04CQEEEEAAAQRiCBAAjQFDNQIIIIAAAggggAACCCBQkAK2GNT7r0gd2+e86iFNXYboOOnGa3IeowYBBBBAAAEE9k6AAOje+XE2AggggAACCCCAAAIIIBC3QId20tTXpL/fk3nKVRdLX02VTumZWccWAggggAACCBScAAHQgrPkSggggAACCCCAAAIIIIBAXAIN6mc2i9zOrGULAQQQQAABBApKgABoQUlyHQQQQAABBBBAAAEEEEAAAQQQQAABBBBIOQECoCn3SugQAggggAACCCCAAAIIIIAAAggggAACCBSUAAHQgpLkOggggAACCCCAAAIIIIAAAggggAACCCCQcgIEQFPuldAhBBBAAAEEEEAAAQQQQAABBBBAAAEEECgoAQKgBSXJdRBAAAEEEEAAAQQQQAABBBBAAAEEEEAg5QQIgKbcK6FDCCCAAAIIIIAAAggggAACCCCAAAIIIFBQAgRAC0qS6yCAAAIIIIAAAggggAACCCCAAAIIIIBAygkQAE25V0KHEEAAAQQQQAABBBBAAAEEEEAAAQQQQKCgBAiAFpQk10EAAQQQQAABBBBAAAEEEEAAAQQQQACBlBMgAJpyr4QOIYAAAggggAACCCCAAAIIIIAAAggggEBBCRAALShJroMAAggggAACCCCAAAIIIIAAAggggAACKSdAADTlXgkdQgABBBBAAAEEEEAAAQQQQAABBBBAAIGCEiAAWlCSXAcBBBBAAAEEEEAAAQQQQAABBBBAAAEEUk6AAGjKvRI6hAACCCCAAAIIIIAAAggggAACCCCAAAIFJUAAtKAkuQ4CCCCAAAIIIIAAAggggAACCCCAAAIIpJwAAdCUeyV0CAEEEEAAAQQQQAABBBBAAAEEEEAAAQQKSoAAaEFJch0EEEAAAQQQQAABBBBAAAEEEEAAAQQQSDkBAqAp90roEAIIIIAAAggggAACCCCAAAIIIIAAAggUlAAB0IKS5DoIIIAAAggggAACCCCAAAIIIIAAAgggkHICBEBT7pXQIQQQQAABBBBAAAEEEEAAAQQQQAABBBAoKAECoAUlyXUQQAABBBBAAAEEEEAAAQQQQKBYCsybN08dOnTwX//9739zfYZff/013Hb37t25to334OLFi+NtulftCvs+Y8eO9TYPP/xwuJ/R6sIH2UAgSQIEQJMEzW0QQAABBBBAAAEEEEAAAQQQKI0CO3aHtHZHulZtT9e6nelK2xNKOYZt27Zp9uzZ/uvKK6/U5s2bY/Zx165d4bah0N49y549e3THHXeoffv2Me9XEAeSdZ8VK1Z4m59//jnc7Wh14YNsIJAkAQKgSYLmNggggAACCCCAAAIIIIAAAgiUJoHfXKBz8cY9WrAhXT9vDWnltpCWbQlp3vp0/bg5XbvT9y54WFiWy5Yt06233lpYl89y3Y0bN+rBBx9UWlpalvqC3knWfQq631wPgYISIABaUJJcBwEEEEAAAQQQQAABBBBAAAEEvMBOl/W50AU+t+6KDrLht5AWbUy9IGjZshlhEhu2/d5770XvPLUIIFDsBMoXux7TYQQQQAABBBBAAAEEEEAAgVIlsGJl5uP+ErGdWctWKgnYsPAfXIZnXiPdf9sjnxl6cM0yKdP9unXr6swzz9S4ceN01VVX6dtvv1XNmjUT7p8N+54zZ44sm7R58+Zq27at6tevn+U6K1eu1Pfff+/rzMzmIbXSunVrBYFYX5HLH3afBQsWaMmSJapXr54OOeQQtWrVShUrVgyflaz7hG/IBgIpKEAANAVfCl1CAAEEEEAAAQQQQAABBBCQ3p0q3f6AtDgjRuRJhj0hveES8x66R+p5PEqpKLDRjebe6YKb8ZSNLhPUskUrl0+dIOgjjzzisz9tHsuBAwfqySefjOdRfJsNGzbo7rvv1ujRo2XzbgalXLlyuuWWWzR48GBVqlTJV//1r3/VqFGj/LbNK3r44Yf77S1btqh69erBqVE/ly9f7gO07777bo7jzZo10/jx43X88Rn/gSTrPjk6QgUCKSRAADSFXgZdQQABBBBAAAEEEEAAAQQQyBAY/ZR0673RNRYukc66THr0b9IVF0ZvQ23BCFhm4mI3VD2RYpmdiZSlm9JVIYEJ+iqWK6ODaiZwQiKdcW0t49OGwJ988sk+E/Tcc8/123ldxqys7dSpU9W4cWMNGDBALVu21Pz58zV8+HA99NBDmjFjhj9epkwZ9enTR/vtt5/uvPNOWYA0WDk9CJDGup/N52kZpRZs7d69u/7whz/Igp4ffvihpkyZoqVLl+qcc87x2adVqlRJ2n1i9Zd6BFJBgABoKrwF+oAAAggggAACCCCAAAIIIBAWmPmV9Jf7w7tRN1ysSTffLbVvK7XLSJyL2o7KvRfYtnvvr5HbFdJcfNW+4i277eUXcjnppJN8hqVlf1599dV+KHytWrVyvevIkSN9cNOCkZ999pkaNGjg25911lm67LLL1KlTJ3300UeaOHGi+vbtqx49evhAZhAAvfHGG3O9fnDQhudb8LNNmzb673//64Onduy8887Tfffd54Ova9eulWWH2r2TdZ+gf3wikIoChfcrk1R8WvqEAAIIIIAAAggggAACCCCQ8gJ/Gy6lxxEQsxHGQ1xbCgKFIWAZmfvvv79suPnNN9+c5y1s2LsVG+YeBD+Dk5o0aeKDk7YfZHoGxxL9bNeunf72t7/5LFXLHI0sDRs21DHHHOOr1q9fH3ko4e1k3SfhjnECAvkQIAM0H2icggACCCCAAAIIIIAAAhkCX8yWfvhJ+m5xpojN1/j8a3JZSS4j6czMerYQiEdgx07po0/jaZnR5r8fS276RFWoEP85tIxfwIZqt6mXWO7Umh3pWrU9/nscXKOMqlcsE/8JSWppQ+EtA9SyQSdMmOCHt5966qlR7757924tXpzxjdDaRytBvbWz+UGzBy+jnROtrmfPnrKvoNi1fvjhBy1cuFBffPGFHwJvx6xPe1OSdZ+96SPnIhCvAAHQeKVohwACCCCAAAIIIIAAAjkExj2XEeyMPPDxZ5J9ValMADTShe34BFautsBNfG2tVZoLfq5eI+3XOP5zaJmYQPmyiQUn96lSVr+6IGh6HCPVK7tflNSqVEYWaE3FYvNr2hB4mxP0mmuu8UPho/XT5t20hYxs8SJbjT1asSzQCi5Sn5aWpp9++klNmzaN1iyuOjvf5hX94IMPfODTrhmU8uULLtSTrPsEfecTgcISSOzXOIXVC66LAAIIIIAAAggggAACCCCAgBOoViVxhqpVEz+HMwpPwAKm+1fPO6BpLQ6oUTZlg5+BkA1ZP+CAA/TLL7/opptuCqqzfFpg04plXdpiSNGKHQuyMoP20drlVTd79my/YrwFQC3r86ijjlL//v19kHbJkiWKlaWa13WzH0/WfbLfl30ECkOg4H4tUBi945oIIIAAAggggAACCCCQ0gK93WjQFjGSmBiSnNKvLmU719CtG9NkX+mXlfF18aD9pbq142tLq+QJ1K1cViGl6+ctIfeZs5R30U9byb1ahbwDpTnPTm5NjRo1/FB4ywZ96qmn1KVLlxwdOPDAA312586dO7V69Wo1atQoR5tly5aFg6P77LNPjuPxVtgCSlu3btWFF17o+2UrvUcWGw5vJT2eiXQjT8y2naz7ZLstuwgUigAB0EJh5aIIIIAAAggggAACCJQOgVNPlOyLEp/A9P9Jq36V/vdlZvv5C6VX3nCZjy6L8ZTMaf0yG5TCrcsvkP72z/gevO+f4mtHq+QL1HNB0JoVQ1q3I6Stu0La4yKh5d041Jpuvs+6lcuoXIoOe48m1atXLz8EfsyYMfrzn/+co4nN59m6dWvNmTNHL7zwQtRMUau30rFjR1Wu7OYIcaVs2YyBufEGK21ho7lz5/pz77//fmUPfm7btk2LFi3yx4Ns02Tex9+YPxBIQQGGwKfgS6FLCCCAAAIIIIAAAgggUDIFhj0hXd5fGj0x8/lefzuj7pZ7M+tK+9aN10iHt8pboe1h0vVX5N2OFkUnUMENh29Uraya1y6nlnXKqVmtcrI5QotT8DPQGzZsmCzTc8uWLUFVls/77rvP7w8ZMsQHQiMPzpo1S3a+lQEDBoQPVf19/gYLVtoQ+7yKtQ/m+Pzwww+zNLfs0zPOOEO//fabr7f9oCTrPsH9+EQg1QQIgKbaG6E/CCCAAAIIIIAAAggggEApF6jqRvS+/rTUoV1siM5HSZMnymXSxW7DEQQKUiAYCh/rmr1791afPn20Zs0ade7cWTaEfOjQobr00kvVtWtXbdq0yS9cdNFFF4UvUalSJTVunLGC15FHHqkOHTpo5crY8z9Y5uj555/vz7/11lt18cUXa/To0bruuuvUpk0bffrpp/4a1iAyoJqs+4QfjA0EUkyAIfAp9kLoDgIIIIAAAggggAACCJRcgQt6S0fHCOrVrlVynzs/T9bIzQU69TXpxX9LDz8uLViScZVDW0q3Xiede7oNH87PlTkHgfwLnHjiierXr5/+9a9/Rb3ISy+95AOS99xzjyZOnOjbVKxY0Q97t4DoFVfkTFl++umnfZB0xYoVPng6b9487bvvvlGvb5VPPPGE7Jo2H+lzzz3nvywrtGfPnnrrrbf8HKTHHXecXn/9dT3yyCPhRaaSdZ+YHecAAkUoUMatTuZm4aAgULIFTj/9dE2ZMsU/5OLFi9W8efOS/cA8HQIIJEXgo48+Uo8ePfy9rr32Wo0aNSop9+UmCCBQ8gXat2+vr776yj+ozecWDF0s+U/OEyIQXeDx8dJtgzOO/fOv0tWXRG9HLQKpJGCZnD/99JPatm0b1/fxVatW+YWU6tWrF9djbNy4UbbquwU/bf5Ry/KMpyTrPvH0hTYIJEuADNBkSXMfBBBAAAEEEEAAAQQQQAABBBAoNQKWxZlbJmd2iGgrx2dvE7lfu3bt8HD3yPq8tpN1n7z6wXEEkinAgIFkanMvBBBAAAEEEEAAAQQQQAABBBBAAAEEEEiqAAHQpHJzMwQQQAABBBBAAAEEEEAAAQQQQAABBBBIpgAB0GRqcy8EEEAAAQQQQAABBBBAAAEEEEAAAQQQSKoAAdCkcnMzBBBAAAEEEEAAAQQQQAABBBBAAAEEEEimAAHQZGpzLwQQQAABBBBAAAEEEEAAAQQQQAABBBBIqgAB0KRyczMEEEAAAQQQQAABBBBAAAEEEEAAAQQQSKZA+WTejHshgAACCCCAAAIIIIBAyRKY8pU05+foz1ShnPTn06IfoxYBBBBAAAEEEEiWAAHQZElzHwQQQAABBBBAAAEESqDAf7+VXpkZ/cEqVyAAGl2GWgQQQAABBBBIpgBD4JOpzb0QQAABBBBAAAEEEEAAAQQQQAABBBBAIKkCZIAmlZubIYAAAggggAACCCBQsgSu6i6dcoT03Qpp2FsZz9a9tXRJV6mcGwJPQQABBBBAAAEEilqAAGhRvwHujwACCCCAAAIIIIBAMRY4fH/JvqpXznyI/etJJ7XN3GcLAQQQQAABBBAoSoGUCYCuX79e77zzTkIWZcqUUeXKlVWrVi3Vrl1bLVq0UPXq1RO6Bo0RQAABBBBAAAEEEEAAAQQQQAABBBBAoOQKpEwAdOnSpbrooov2SrpChQrq0qWL7rnnHvXs2XOvrsXJCCCAAAIIIIAAAggggAACCCCAAAIIIFD8BUrUIki7du3StGnT1KtXLz3++OPF/+3wBAgggAACCCCAAAIIIIAAAggggAACCCCwVwIpEwDt0KGDtm7dqmOPPdY/UI0aNXTXXXfpvffe0+LFi7Vy5UrNmDFDL774onr06BF+6Pvvv19vvPGGnn32WV199dWyYfGhUEg333yzvvrqq3A7NhBAAAEEEEAAAQQQQAABBBBAAAEEEECg9AmkzBB4C1zeeuutmj59utq3b693331X9evXz/JGGjVqpKOPPlrnnXeennvuOV188cUaO3asZs+erQYNGvgh9JdccomvX7ZsmUaMGKEJEyZkuQY7CCCAAAIIIIAAAggggAACCCCAAAIIIFB6BFImA9QClqNHj1aVKlX0yiuv5Ah+Zn8lNl/oNddco+XLl2vIkCHhw8cdd5z+/ve/+/3XXnstXM8GAggggAACCCCAAAIIIIAAAggggAACCJQ+gZTJAP3888+9fseOHXXwwQfH9SbOOussjRkzRsG5wUknnnii39y8ebM2bNigOnXqBIf4RAABBBBAAAEEEEAAAQSKTGDJamnT9ui3r+R+Ojt8/+jHqEUAAQQQQACB/AukTAB03rx5/imaNGkS99PYsHcr3333XZZzateurbJlyyo9PV1r164lAJpFhx0EEEAAAQQQQAABBBAoKoH73CC1j7L++BLuyn51pS/uC++ygQACCCCAAAIFJJAyQ+Btfk8rs2bNivvRgratWrXKcs7MmTN98NMqg+tmacAOAggggAACCCCAAAIIIIAAAggggAACCJQKgZQJgB511FEefNGiRRo5cmSe+OvWrQvP/WkryEcWWzneSt26dWWryVMQQAABBBBAAAEEEEAAgVQQON7lbpzXSercPLM3h7lBcFb3x3aZdWwhgAACCCCAQMEJpEwAtFOnTurSpYt/soEDB2rQoEF+/s5oj/r222+rZ8+esoWTypcvrwsvvNA3S0tL0xNPPBEOoJ5xxhnRTqcOAQQQQAABBBBAAAEEECgSgWt6SI9cJF3SNfP2J7XNqLvrrMw6thBAAAEEEECg4ARSZg5Qe6QJEybo2GOP9fN2Dh06VCNGjJANbz/ooIP86vA///yzfvjhBx/4DAiGDx/uz7H9UaNG6aabbvKHbA7Q2267LWjGJwIIIIAAAggggAACCCCAAAIIIIAAAgiUQoGUCoC2bNlSU6dO1ZVXXimbx3Pbtm2aPXu2/8r+burVq6e7775b119/ffiQDZ+3UqtWLU2aNMkHT8MH2UAAAQQQQAABBBBAAAEEEEAAAQQQQACBUieQUgFQ02/Tpo3+97//yYa5z5gxwwc/v/zyS61cuVL777+/DjnkEPXo0UMDBgzIMb+n1dvQeBtKv++++5a6l8kDI4AAAggggAACCCCAAAIIIIAAAggggEBWgZQLgFr3ypQpo1NPPdV/Bd3dvXu3n+8z2I/2ee6550arpg4BBBBAAAEEEEAAAQQQQAABBBBAAAEESqlAyiyClJe/LXZEQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEhEoNgHQRB6KtggggAACCCCAAAIIIIAAAggggMDeCFx33XXq0KGDunXrprS0tHxdauzYsf4aDz/8cPh8W7PErjt48OBwXbCxZ88ev/hzsB/5uXjx4shdv23Xsa+tW7fmOEYFAghkCqRkWmV6errmzp2rNWvW+G8yoVAos8cxtk477bQYR6hGAAEEEEAAAQQQQAABBBBAAIGiEtj6m/TLRmnnLqlaJWn/OlKllIxGZArZOiRjxoyRBSStTJ48Weeff35mgzi3VqxY4dc2OfbYY8NnrF692te1bds2XGcbs2bN8otCX3DBBbrjjjvCx6wPd911l0aOHKktW7aE623DFo62YtMGUhBAILZAyn3LefTRRzV8+HD9+OOPsXsd5Ug8QdIop1GFAAIIIIAAAggggAACCCCAAAKFIGCBzw8WSgtWZ714uTLSkftLxzeXKpTLeixV9p5++mkf/OzTp49efvlljRo1Kl8B0GjPc+SRR6p///7q1KlTlsNPPfWU5syZIwuARpaNGzfqwQcfVMWKFSOr2UYAgQQEUioAar9duemmmxLoPk0RQAABBBBAAAEEEECgqAUWrZQmfZbZi8/cKM3350onHm4LnGbWs4UAAqVHYNMO6dmZkgVBs5c9bpDnrGUZWaEXdJAqpmAQdPz48b7bQ4cO1SeffKKPP/5Y8+fP16GHHpr9cRLe7969u+yLggACyRNImQDounXrdOONN4af/LLLLtMRRxyhgw46SFWqVAnXs4EAAggggAACCCCAAAKpIbAnXRr6H+lfH0qRs1YtddlefcdKHQ6WRl8hNaqVGv2lF8VPoNuZ0jfzJDdLWrjccq/05/vd368jpP++Gq5mI4UE7PvBv+dED35GdnPlZvcOF0inHhZZW/Tb06dP16JFi9SiRQs1a9ZMlgX62GOPafTo0RoxYsRed9DiH6tWrVKdOnXUuHFjn2m6YMECrV+/3l/bhsjPmzdP9evXd3/30/X999/7ehv5avVWWrdurbJly/rtWH/YufYc33zzjR8i365dO7Vq1UrlyqVgxDnWQ1CPQAEJpEwA1Oa62Llzp3+sCRMm6PLLLy+gR+QyCCCAAAIIIIAAAgggUBgCd70iPTM99pVn/SCd62IFb94i1aoaux1HEIglsMtNa5h9akMLhtrX7oypGWOdSn0RCixdK1lwM54yd4V0TFOpdgrlPQXZn7179/aP8Kc//ckHQG1YvA1Fr1p1776h2XUGDhyovn37yu5lAdHDD3cp878XmxrQvm655RZt377dD7+3Q7t27Qq3s7lAq1evHpyS49MCpRdddJEPfkYetPs899xzyj7/aGQbthEoiQIpEwD98ssvva/9hsOyPykIIIAAAggggAACCCCQugI2zD234GfQ8x/XSA+9Kf2tT1DDJwLxCzRpJG2OEUhr7I5RCl8g3WVzvv5NYvf5Nes6PXme/NrXiQVAa1SWerXK87L5amCrqb/00kv+3CA20aVLF58NatmUzz//vF+oKF8Xj3FSjRo1/Foor776qh9ub4s89+rVS+3bt/eZm/vtt5/uvPNOn7kZrCZfqZJbTSpGmTlzpo4//nifZHbOOefo7LPP9tmi77zzjmye0Y4dO+rTTz/VUUcdFeMKVCNQ8gRSJgBas2ZNr2sp2WWYKKjk/U3jiRBAAAEEEEAAAQRKlMDEafE/zgufS3e5ocxVWL8jfjRaeoGXxwFR1AI2nH2x+0VGYZY1WyX7irfU3bsEzFxvY8HPbdu2+SChDTMPLa/xcQAAQABJREFUio1SHTRokM/GvPLKK4PqAvm0af9sSsAlS5b4AGjXrl2zTBFo2ZpBADRy6sBoN7dh8gMGDPDBz/vvv1/33HNPuJktrtSmTRvdeuutvo0FQSkIlBaB3CeMSKKC/UbFSqKrvyexi9wKAQQQQAABBBBAAAEEfheYmTElXVwev7lhzN8uj6spjRBAAIEiFRg3LiPqnn1avksvvdRnUc6ePVuWYZmq5aOPPtIXX3yhJk2a+KBp9n5ec801qly5sj777DPfLvtx9hEoqQIpkwFqv9GoV6+e/42H/QfLimgl9a8cz4UAAggggAACCCBQEgQ2uxWeEym2IjQFAQSKn0A5lzZ1ZUa+Utydn+Pm9Zz5U9zNdZJLtNyvdvztyxdSKpctRGSBQRtebtmSkcUCijYs/d133/WLIR199NGRh1Nm21aqt2ILStvq9dGKzQNq67DY83bu3DlaE+oQKHECKRMALV++vP7973/7byg2EbAthEQQtMT9feOBEEAAAQQQQAABBEqIQEO3svuydfE/TKOMGa/iP4GWCCCQMgL1Y6+1E7WPRx8gffWzW6jKLVaVV6nlFj9q01iyQGtRF4tDWNmzZ094saHIPm3+fULaF154QTYXZ+3aCURtIy9UiNuLF7sJml2x4e09evTI9U425J6CQGkRSJkAqK1glpaWpuuvv17Dhg3z/6Hab1SaNm2qAw44wP8GJreX8te//jW3wxxDAAEEEEAAAQQQQACBAhTo5jK24lkEyW65Tw3p0CYFeHMuhQACKS1gixR1P0T678Lcu1nGHT7ZfS9JheDn7t27ZauzW7E1Smw/e7HV33fu3OlXZrfFhPKajzP7+cnYtzlArVjw8/TTT8/1lkceeWSuxzmIQEkSSJkAqKVen3DCCVlsbV6NeOfWIACahY4dBBBAAAEEEEAAAQQKVeBa97/utrjRrj153+b6XnJz5+XdjhYIIFByBI5yWaCWAfqxS0jMCMllfbYK5aQ/Hu6GatfLWl9Ue2+99ZZWrVqlOnXqaOXKlapYMfqqbTfccIMef/xxPww+FQOgLVq08IS2svzNN99cVJzcF4GUE+B/Q1LuldAhBBBAAAEEEEAAAQRSX+DA+tJDf5Isgyu3cnJb6Yrjc2vBMQQQKKkCnQ6SrjpG6uCCoQ1dJngtlxnaxE2f0bWp1O9YqUWD1Hny8ePH+86cd955MYOf1iBYAd6SuGz9koIsZX//TZENwY8sQX16uoso51Fsfk8r06ZN09q1a3O03r59uzp16iRbiPrDDz/McZwKBEqqQMpkgLZv314bNmwoqc48FwIIIIAAAggggAACJU6gT0epbjXpzpel5euzPl5F95OGZYnecirZn1llMvYiF4XatD1aC+oQKBkC9j2iZ8vUfpbVq1frzTff9J285JJLcu2sDRtv166dvv76a40aNapA1y6pUsVNiOrKTz/9lKUPNvTeig3L/+WXX/wK71kaROx069bN98mCs/369dOzzz6r4LrW7Pbbb9eMGTNUvXp1HXXUURFnsolAyRZImQBouXLlUnIC4ZL9+nk6BBBAAAEEEEAAAQT2TqDnYdLxraQnXSLR3/6Tca1j3QjMUX2lOi7wQckq8N0K6a+vu+ysBZn14z52K2Z/7wLJZ7rMOGdHQQCB5Ao888wzPrhoa5B07do1z5tbFmj//v01efJkWfC0YcOGeZ4TT4NmzZr5ZpaNatMBnnHGGRo8eLBfE6Vx48ZasWKFLABr66S88cYb2nfffaNeduTIkbJA6GuvvaYjjjjCX6dChQr+nHnz5rkpScpq3Lhxfq7TqBegEoESKMAQ+BL4UnkkBBBAAAEEEEAAAQSSKWBz+bV1Q1yDcrAb1krwM9DI/PxwvnT6w1mDn8HROT9LF4yMf2Gp4Dw+EUBg7wWC4e8XX3xxXBe76KKLfFBy165devLJJ+M6J55Gl19+ufr06aPy5cvrm2++0dSpU8On2QJNFgRds2aNZs+eLQtkxiqHHXaYP37OOef4bFJbsf7BBx/0dRZAnTJlimyoPwWB0iRQJBmggwYN8sb2H7X9NsPK8uXL9cQTT/jt/PwxZMiQ/JzGOQgggAACCCCAAAIIIIBAoQv84qYI6Dde2rkr9q1soRibTqB1YzdnopsjkYIAAskRmD/f/XYigWILJdlq8PGUe++9V/YVWWxxomgLFFmW5ksvvaS0tDS/EFNkhmfPnj398HdbqMna1auXsXpUsOp75PVt27JSX3nlFZ/ZunjxYm3cuFEHH3ywGjVqlL0p+wiUCoEiCYAOHTrU41auXDkcALVV1oL6/MgTAM2PGucggAACCCCAAAIIIIBAMgQee1/anpb3ndJdFPQhNxXhS/3zbksLBBAomQK2Av2BBx4Y9eESDWBa4lnr1q2jXotKBEqTAEPgS9Pb5lkRQAABBBBAAAEEEECgSATe+Sb+236+RNqwLf72tEQAAQQQQACB3AWKJAN08+bNvldlypQJ985WHwvqw5VsIIAAAggggAACCCCAAALFXGD7b9LarfE/RMhlgS53Q+aZRzV+M1oigAACCCCQm0CRBEBr1KiRo0+2Cpl9VavGUpE5cKhAAAEEEEAAAQQQQACBYitQIR8/dVXKxznFFiiXjt/0rPT9r9EbtHBTGQ67MPoxahFAAAEEEIgUSJl/VtetW6emTZvqmGOO0Z///GedcMIJkf1kGwEEEEAAAQQQQAABBBAolgIVykkt95UWroyv+1UrSgfWj69tSW/13Qpp3vLoT2mZshQEEEAAAQTiEUiZOUBfe+01PwT+nXfe0dy5c+PpO20QQAABBBBAAAEEEEAAgWIhcH6n+LvZu4NUqUL87WmJAAIIIIAAArkLpEwGqK0CH5Ru3boFm3wigAACCCCAAAIIIIAAAsVe4LLjpFdnxc5mDB6wQU3p1lODPT5fu1HavUd6Zrr04JQMj7vPki7oLJV3mbUUBBBAAAEE4hFImQzQyCHvX3zxRTx9pw0CCCCAAAIIIIAAAgggUCwELKPz6X5S2/1jd7dJHWnSddI+LghKyRCoVkmqVVWq7KYFCEoVZ2l1doyCAAIIIIBAPAIpEwC1uT8vuOAC3+fBgwfrvffei6f/tEEAAQQQQAABBBBAAAEEioVAw1rSfwZKQ8+XmjbI7LJlfd5+ujR1kNSqcWY9WwgggAACCCBQMAIpMwR++/bt6t+/vypXrqyJEyfqpJNOUsuWLXXIIYeoefPmql8/91nA77zzzoIR4SoIIIAAAggggAACCCCAQCEJ2LDtS7pKNStL1z+VcZOL3f4NvQrphlwWAQQQQAABBJQyAdDvvvtOXbu6f/kjysKFC2Vf8RQCoPEo0QYBBBBAAAEEEEAAAQQQQAABBBBAAIHSJZAyQ+BLFztPiwACCCCAAAIIIIAAAggggAACCCCAAALJEEiZDNB27dopciX4ZDw890AAAQQQQAABBBBAAAEEEEAAAQQQQACBki2QMgHQChUqqFGjRiVbm6dDAAEEEEAAAQQQQAABBBBAAAEEEEAAgaQKlIgh8KFQKKlo3AwBBBBAAAEEEEAAAQQQQAABBBBAAAEEiodAymSARnLZivC2+NG2bdu0e/fuyEPas2eP/0pLS9OGDRv07bff6vnnn9eyZcuytGMHAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIqQCoBTvvvfdejRo1ygc3eT0IIIAAAggggAACCCCAAAIIIIAAAggggMDeCKRUAHTYsGEaMmRIQs9Tvnx5de7cOaFzaIwAAggggAACCCCAAAIIIIAAAggggAACpUMgZQKga9eu1f333+/Va9asqeuuu06tWrXyw9vfffddXXDBBTr55JO1fv16ffHFF3r55Zdlc3+OHj1aV155Zel4WzwlAggggAACCCCAAAIpJvDqTOnrn6SVGzM7NmOpdPcrUoVy0j29M+vZQgABBBBAAAEEikIgZQKg8+fP186dO73B22+/rWOOOcZvlytXThYA3bRpky677LKw0emnn67LL79cd955p8455xzVrl07fIwNBBBAAAEEEEAAAQQQSI7AJwukV1wQNLIsXCnZV+UKBEAjXdhGAAEEEEAAgaIRSJlV4BcvXuwFjj766HDw0yq6dOni66dNm6b09HS/bX9cfPHFeuyxx7R69Wrdcccd4Xo2EEAAAQQQQAABBBBAAAEEEEAAAQQQQACBQCBlMkB//PFH36dDDjkk6Jv/POigg1SxYkW/IvzSpUsVebxPnz66/vrrNWnSJD3xxBMqU6ZMlnPZQQABBBBAAAEEEEAAgcIVuLan1LtD9HuUS5l0i+j9oxYBBBBAAAEESodAygRAGzVq5MVtUaPIYkPgmzdvLhsiP2fOnCwB0Pr16+vQQw/VvHnztGzZMh144IGRp7KNAAIIIIAAAggggAAChSzQqrFkXxQEEEAAAQQQQCBVBVLmd7K24JGVH374IYdV69atfZ0FQLOXqlWr+ioLglIQQAABBBBAAAEEEEAAAQQQQAABBBBAAIFIgZQLgH766aeaO3duZB912GGH+f0PPvggS/2qVas0a9YsX1ejRo0sx9hBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRSJgDapEkT9ezZ0y901KNHD40ZM0abN2/2b8j2rVhw9JFHHvFtVq5c6Rc/CoVC/pgNk6cggAACCCCAAAIIIIAAAggggAACCCCAAAKRAikTALVOjR8/XpbJuW7dOvXr108vvPCC72v37t115JFH+u1bbrlFDRo0kC2ONHHiRF934oknat999/Xb/IEAAggggAACCCCAAAIIIFCyBNJ2Zz5P5HZmLVsIIIAAAgjEFkipAOgBBxygV199VUcffbTvcbNmzcI9t2BnEOS0AGlaWpo/VrduXf3zn/8Mt2MDAQQQQAABBBBAAAEEEECgZAgsWS1d9aT04BuZzzP4danfeOn7XzPr2EIAAQQQQCA3gZQKgFpHe/XqpRkzZuizzz5Tu3btwn1v27atrxswYIBs2xZNuuyyy/TNN9/o8MMPD7djAwEEEEAAAQQQQAABBBBAoPgLfODWuT3lIekdtxZuesbMZ/6hbPvNr6WT3bFpC4r/c/IEqStw3XXXqUOHDurWrVs4CSt1e5u/ni1cuNA/49lnn52/CyThrD179kRdMDsJt+YWEQLF/T2kXAA0sO3SpYvq1asX7PpPG/b+6KOP+qDnd99954fA77ffflnasIMAAggggAACCCCAAAIIIFC8BX5YI/3fBGnHrtjPsd0NCrx6nPTzuthtOJIaAjvde5z7i1vX43tpwSppT3pq9Cu3Xti6I7Y2yezZszVt2jRNnjw5t+bF9ti2bdv8M3777bcp+Qy28HX79u3DUySmZCdLQadKwntI2QBoKfj7wyMigAACCCCAAAIIIIBAKRO4xgXsWv1FumVS5oOPfD+j7sShmXWlfevhtyQLcOZVtv0mPfJ2Xq04XlQC9n4e/1jq46YxuNXFDwe793rjK9J57r+D52eldiD06aeflmW89enTx/ONGjWqqBhL9X2feuopzZnj0sApRSpQEt5D+SIVjHHz9PR02W8f1qxZ41eCD1Z6j9HcV6dyunZu/eYYAggggAACCCCAAAIIlB4BC+pt3Zn1eW1RH/va6oJFFGnXHundufFL2BD5YS6jsBzpPfGjJaHlhu0u6PmatHxjzpvZ3/WJX0hzXFbo4D9KFcrlbFPUNbZIs5WhQ4fqk08+0ccff6z58+fr0EMPLequcX8EEMiHQMoFQJ977jnZPJ/r169P6HHiCZImdEEaI4AAAggggAACCCCAAAIFLFC7qtSgZvSL1q8evb601a5yAbMdcWR/Bi5bXEB5zRapUa2ghs9UEBj6bvTgZ2TfvvxZevIzN93BcZG1Rb89ffp0LVq0SC1atJAtzmxZoI899phGjx6tESNGJNRBW8R51apVatKkiWrXrq1Nmzb5gOqOHTv83KINGjQIX++3337TF198ocWLF+uQQw7Rcccdp7Jlo0f2d+3a5TMjLShbvnx5v1ZKy5Yt/Xb4glE25s2bp5kzZ+qII47w50RpkqXKEtTMwtZf2b17t1+rxdZkKVcuZ9Q66Iu5/fjjj/45u3btqqZNm2a55s6dO/01bf5R8zBju2aw8LU1tuzbBQsWhGNDq1evlvW9fv36atiwYZbrbdy4UV9//bV3s3vZejLZp1TMckIuO/H0LTjdpmY0B3tei0nZ85utBcmPOuqoLEbLli3zQfQqVaqoU6dO2n///YPL5PhcsWKFf7d2TvPmzf17sueOVszESuvWrXP8XbFnWbp0qSpWrOj/PgXnW7/t75X9fbF+23v43//+J1tk3PrduHHjoGlC7yF8UqpuuIdNmTJu3LiQewk2vXXCXynzEHQkJQX++Mc/hv9OuX9MUrKPdAoBBIqfwIcffhj+3nLttdcWvwegxwggkLICRx55ZPj7i5ufLWX7SccQKAyBX9aHQk36J/a1ZnNh9IRr5ldg9rJQ6A+Pxfd18shQaM2W/N6pcM7r27ev/x582223+Ru4RZr9fq1atUKJfk8eNmyYP3fs2LGhe+65J+QCZuHv7xb7uOGGG/w93n777VD16tWzHOvYsWPo119/zfGQb731VsgF3bK0tWu5IGLIBbJytLeKZ599NnTggQdmOccF6kKvvvqqr3MB1xznuZG5IRcozXKO3cctRB1yAdEc7V2gLXTAAQeEXnvttSzP+fDDD4fbPvnkk6GaNWvmuKbFgsxi+/btvq0LeOZoY/e+5ZZbwtdyAdnQ4MGDQy4AnKWtGZu1CxKH28azEW/fgmvZ+3KB7ZALMoZcoDJLH1wANuQCiyEX6A5FxiPsGSpXrhxywfTgMuFPlwgYuv7667PYWXt7nr/85S8hF9AMtw027Lh9bdiwIagKf7r5a/0xFxQO19mG9btRo0ah5cuX+3cZXMM+y5QpExo0aFDIbK3E8x58w2LwR8pkgNpvOv7v//5P9tuFChUq6KqrrtIxxxzjfwMQ6zce7uVQEEAAAQQQQAABBBBAAAEESpBAQ5fJaZmyG90Q6niKZc7WI3s2Hqp8tbEFix77KLFT562Mv326C9EMcdmiB9SJ/5y61aRLO8XfPpGWW7du1UsvveRPueyyy/ynLdJsWX6WCfn888/ryiuvTOSSvq0LhGrJkiU655xzdOyxx+qdd97xXyNHjpRlc06YMEGnnnqqTjrpJFnm3xNPPKEZM2bo7rvv9pmnwQ0/+ugjnXbaaT5z7/zzz5cLrvk4yuuvv+4XarI4il37xBNPDE7xWaVXXHGFz+a76aabfGapZQY+8sgjuvDCC8PtIjcsk/H444+XZRFan23aQYvN2LVtPkgXnNWnn37qMwYjz9uyZYuuvvpquSCfz8S0RaROOeUU38QFK3Xvvff6LM5+/fp5B5v6cMqUKX6hKbNwQVrdeuutqlGjhoYPHy4XoPWZpPbMvXr18gsiBfc777zz5IKtsixaFxj1WZCWPWtZunYvy4585ZVXgua5fibSt8gLbd682T+HCyrKBQ59Bq4LdssW0TIzy1a1KR7vu+8+7bPPPr6/H3zwgW688Ub/rm2xbysufqhzzz1XU6dO9RmYNjLaMjQtq9QcHnroIf/3wY67IKU/Z2/+sL/nlp1r97Vnt77ZtV9++WUNGTJEBx98sI/LxfMe9qYfST03VYK07j8cH5l2Dx+y32ZQEChIgcjfuJABWpCyXAuB0i1ABmjpfv88PQKFKUAGaGHqcu3iIHDnS/FngN73WnF4ouLbx10uESzebM5ktbvymcLztJGpFpew7MvI4oJCvt4NEY6sznM7yAC1a/7jH//I0t4FUsNxkCDbNGjgAlH+mGVUBsUF20IuYObrI7Mqg+MuyOaPWTZnkC1o57ghzb7eBW+Dpv7TMgBd4Ct8TnDQJaaFOnfu7Ovvv//+oDr8GTyTC7aG62zDMkDtOa2Pbli6P2YZkFbsM7iXCzD7usg/LPPRzrWM08hiWaFWb/6RxTJmrd4yGd0UA5GHQmvXrg07vfvuu1mORdvJb9+CjF3LrHWB3PClf/75Z98365+b9iDkgqHhY5aVGmTVunlmw/UuaOvPcdMB+KzL8AG3Ye/JMk3tepHnWBurs69EM0DtHMsizp7RHLwHe/+RJdZ7iGyT6tvRJ5NwEskuLqXc37JNmzbh3w4kuw/cDwEEEEAAAQQQQAABBBBAoOgFbjpZ2qdG3v2weT8H/CHvdrRAIF4BFwD1TS+//PIsp1x66aU+A9IyGi07MtFi81taZmNksQxLK5bRd+edd0YekgtA+X0X/PJzb9qOZV/a3Jo2X6ZlEGYvloFomXuWBfnGG2/4w9Zfm1PS5vy84IILspxi85LefPPNWepsx7JMbS5SO569X3b8mmuu8RmeFsexdtnL7bffLjddgK+2TFArLtAmF0z12YU2p2r20rt3b18V73owtjiVFcuszD4nqM3/GWS2WpZrXmVv+2bukXN07rfffv492H1tdLML0oa7YPO1dujQwe/buwyKzS9rxbIxI+eFtTp7D/acVlzg238WxB/2bqtWden2EeWss87yez/88ENEbcnYLJ8qj2HD3q1ETraaKn2jHwgggAACCCCAAAIIIIAAAskTqO+Cn8/+nxvm/C9p9abo9923tvTMtVIdNxyaUngC5Vza1LCzE7v+f79zwTr3FW/p62J9h2Wuu5LnaZULKZJhi+5YUK9SpUpRg4U2BNtlFPoh6UcffXSe/YxsYAv9ZC+20JEVC47aUOPIEgT1bJpAGyJvgTNbvMaKDW+3xXeyF4ur9OjRQxa8Ctra4kVWbNh9tPKHP/zBD92OPGbDrq24TE4//DzyWLDt5gHVrFmz/EJFQbA2OGYB2uzFgpI27WFkcVmLflqBuXPn+mHwdswWWoqnBH00BwvYZi/Bgkr2TvMqe9u3WO/W3oNNnZC9BO/WphewYs9sQWsrNgVCtBLUWztbICra+492Xm510d6Tyzj2p6SlJbASXW43SaFjhfRtI/EnDL552MpTBfUyE+8FZyCAAAIIIIAAAggggAACCKSCwGH7Sf+9XRr9gQuGfiZt+n1OUAt4XtxVuvYEqVbW5KVU6HaJ64NLTlSbBIKTBrCPm5P1/YVuJW83f2hepZ57n2e3kyqmQHTC5uG0YjEJC/BlLzbfo5UXXnjBZ+LZqu7xFgsmZi/BXI5BtmTk8ci1UIJ2QVAz2rWCcy0D1EoQUAsCoJaVGK1Eqw/OtTk+LaCaW7F5TbOX7Ku+B8fN1eb0tCzbOXPmyA1dDw7luXp9uKHbsFXf3TB3X2XzjeZW3HB02ZozFtTOrexN36K9j+Cd5fZugzY2H6sFuW0eUQvGRiuWBWoBbgtM/vTTT4plHO3cWHVBkDjyuK0Yb8UNZ4+sLhHbKfAtJsPRzXPkf+thE8W+9957DIMvEX+9eAgEEEAAAQQQQAABBBBAIP8CFuy84wwXUKvphrq+lnGdP5/qMkOPy/81ObPwBRq593WxS5B86n953+v6bqkR/LQsvKefftp32K1SHjUT0YYLW9aeW6ncLwQUbRh6rCcOhoJHHo83yBS0C0bOWrAsVnHzWfpDQdtgiHOsc4J2kdcL7mfBz9NPPz3yUI5ti+VkL9GCjXZNm0Zg0qRJvrkFXm0ovA3NtyHhZm4LOMVTgv5Z2wcffFBB0C6ec6O12du+5ffdBs8RvAP7O2h1QWA0sq92zL6sBO0jj0fbtsBvbiUyyJ5bu5JyLGUCoFWqVNGLL76oE044wf9HYKuu2QpoFAQQQAABBBBAAAEEEEAAAQQQKF4Cf3LTHG53o2hf/ip6v21o/YDuUtem0Y8nu9YtxuwzEuvUqeNX8I4VVHOLwejxxx/3w+ATCYAWxPMEQ+Yj547Mfl3LDrQSzCPpFm3y+0G934n4I1p9MGzbhuVHmyM04vS4NydPnuyDn5YR+Z///MevMB95sq3mbsWG/OdV7B3ZnJuWBWpD+KMFYfO6RuTxguxb5HXj3XaLKPmgpgXXV69enWXO0OAay5YtC2dl2ortQbGh8Ja9Gi3A/f333wfN+HQCRRIAveeee8IvLvtbaNmypebNm+d/y2D/cdu+fVqANLfy17/+NbfDHEMAAQQQQAABBBBAAAEEEEAAgSQJ2ND5q9xUBce6qS//PUeau0La4hLS6rppC9rvL53jEgcbZ6yTk6Qe5X4bt7q2b3DeeeflmlHoVm73AVCbW9LmnuzevXvuFy7Ao8GwfAsg/vOf/8wRJ9m0aZPc6uj+jsECS8GCOxbgtezQ7LEVW1gpewnuM23aNB9kjFzgx9paBqxlh1oGoVudPc9h8nbOxx9/bB/64x//mCP4afVffZURKQ+yHK3OSpClaEG+yGJ9NH8bUh8tAPrkk0/6aQo6duzos3Ujz82+nd++Zb9OfvctiNm6dWs/LYBNr3DTTTfluJTVW7Hnicw4tWkY1q1b5wOnkYFRa/vtt9/aR4GUWO+hQC6epIsUSQA0nmClRf0XLlzov+KxiOea8VyHNggggAACCCCAAAIIIIAAAgggUDACrRpJ9pXKxbLu3nzzTd/FSy65JNeuWrCtXbt2+vrrrzVq1KikBkDPPPNMH+yzYKGtKD9ixIjwYjiWAWiBM1tF/bDDDvMLJdmDHHrooX5ouS3udMcdd/jAaTDE2oK4w4YNy/G83bp1889lAcZ+/frp2WefzRI4tVXeZ8yY4eesDDJMc1wkW4UNcbfyySef+KHctqhTUCw4+/e//93vBgsDBceCgG32TNV7773XB0Ct/5YFGgR87TxrO3DgQG3ZskUW0M6r5LdveV03keO2yvvZZ5/tA8o2Mrpt27bh022xqeA9DRgwIFxvG5Y0aO/2/vvv18svvxw+ZkFdC5IXVIn1Hgrq+sm4TubfuGTcjXsggAACCCCAAAIIIIAAAggggAACKSTwzDPP+KCcLSzTtatLW82jWBZo//79ZUOnLXgarOqdx2l7fdiy8J544gkf8LPPL774QieffLIfNm5BRFtYyFb2/uCDD8LzRFp24euvv+4zBx999FG/crutKL5ixQo999xzfi0WC5pmLyNHjpQFQm1ous3TecYZZ/hrvvHGG37UrvXFFjMKgofZz8++f/755+sf//iHbCh3p06ddNZZZ/mFiSxQZ/21oLL1f9u2bbJM1mDxoGCFdcvQnTlzpu/H4MGDfYD22muv9VMRWDbqueee64OGX375pV9XZuvWrf4+f/nLX7J3Jcd+fvuW40J7UdG7d28/HaQFMTt37izrk01FYAtf2XSRtvjR8OHDddFFF2W5y3XXXecDoK+88op/fntn5vj555/7bFt7XwVRYr2Hgrh20q7hJlhNetmwYUOooL+S/hDcsFgJuDR7W8LMf7kV7YpV3+ksAgikrsCHH34Y/t7i/gcsdTtKzxBAoNgJuAyj8PcX98Ngses/HUagoAXGfhgKNemf8fXUtIK+Otcr7QJu+LH/nuum64uLwgUMQ26hH3/OAw88kOs5LnPPt7vqqqtytHOZe/6Y3T97cUPB/TH7OdYNOc9y2M0BGnJBzJDLogy3cYsKhVz2asgFNrO0DXbmz58fcosMhdu7AGbIZRqGfvjhB1/nph4MmoY/3SrtoXPOOSfk5kMNn2f9sX+jXMA13C7YCNq5oHBQleVzypQpIbdKfZZrublKQy6TNeSGuId69uzpj02YMCF8ngv8hdxiSeE+uAB1+JhtuCBuyJ49+HnfPl22YsjNzxqy9xRvyU/f3Krt/r7Lly/PcRuXleqPueBljmN33XWXP+aCszmOuazikBvKHn4eMz322GNDLtico21QYV5u9fjwOW7u1pCbqzZkf4fcgkkhF9gPmvrP3Pod/H1wQ+uznJPXe8jSOEV3yli/3F8QCgIlWsBWrnPf0PwzugComjdvXqKfl4dDAIHkCNiwIPuNsxX7DbQNg6IggAACBSHQvn378Hxolg0TrOJbENfmGggUR4EnP8pcBX5IH1aBL47vkD4XvICt8m0Zgi6gFffPuDY8/JdffvFD423+yHiKzctpP0dv3LhRLoAZdZGeeK5jbWwuT+uDZaBaVuG+++4b16mWAbly5UrfPtoCVTYPpk2jaAskWR8j58mM6wZ70bd4r59IO3tWc7Kh8PH+P8DSpUv9sP82bdqEp0ZI5J7xtM3rPcRzjaJqwxD4opLnvggggAACCCCAAAIIlACBMdOl6UujP0gl99PG2Kyj9aI3pBYBBBBAIGEBl4Xqh44ncqKtOG5fiRSbr9MW6SmIYkPybaoB+0qkWNAzt367DEg/12ki18zeNr99y36dgti3wHC8weHgfsEw9WC/MD7zeg+Fcc+CumaxC4BawmowYW9BIXAdBBBAAAEEEEAAAQQQyJ/Aph3S6i3Rz7UAKAUBBBBAAAEEEChqgbJF3QG7v6Vs/+c//4nZlUmTJqlLly5y8xioWrVqsiFBNuFv9tXBYl6AAwgggAACCCCAAAIIIFAoAuXcTxTl3VfZMpmXt02rsy8KAggggAACCCBQ1AJF+r8kbvEIvxLZoYceKjexrrJPR5qenq6rr77ar3Jlq5vZKl47duzw8yFdf/31Ov7447VmzZqiNuT+CCCAAAIIIIAAAgiUWoGBPaU3r5OGnplJcNrhGXWvXZNZxxYCCCCAAAIIIFBUAkUWAHUrdcmtiqWZM2f6Z7dJdTdv3pzF4fHHH9eTTz4ZrrP5D9wqZXKrWPk6O9et7i0LlFIQQAABBBBAAAEEEEAAAQQQQAABBBBAAIHsAkUSAP3xxx99ZqcFPa2ceOKJGjFiRJZVumx1sbvvvjvc3+HDh2v58uX64IMP9Ouvv+rkk0/2x2bMmKGxY8eG27GBAAIIIIAAAggggAACCCCAAAIIIIAAAggEAkUSAB06dKgfym6dGDlypN5//331799ftoJZUF599VVt2rTJ71qA9MYbb1TZshndrV27tiZOnKgGDRr44wRAAzU+EUAAAQQQQAABBBBAAAEEEEAAAQQQQCBSoEgCoJa1aeWkk06SzeUZrVgANCgPPPBAsBn+bNiwofr27ev3Z8+erV9++SV8jA0EEEAAAQQQQAABBBBAAAEEEEAAAQQQQMAEkh4AtWHv8+fP9/pXXXVV1LdgbT755BN/rFGjRn6hpGgNDz/cza7+e/n++++DTT4RQAABBBBAAAEEEEAAAQQQQAABBBBAAAEvkPQA6IIFC5SWluZv3rRp06ivYdasWX7FdzvYo0cPlSlTJmo7Wz0+KKtXrw42+UQAAQQQQAABBBBAAAEEEEAAAQQQQAABBLxA0gOgS5cuDdPXq1cvvB25YQsdBaV79+7BZo5PWygpKJUrVw42+UQAAQQQQAABBBBAAAEEEEAAAQQQQAABBLxA0gOghxxySJg+Vtbme++9F27Tq1ev8Hb2ja+++ipctc8++4S32UAAAQQQQAABBBBAAAEEEEAAAQQQQAABBEwg6QHQli1bKsjWXLJkSY63sGXLFn3++ee+vnnz5jr44INztAkqIgOgBx54YFDNJwIIIIAAAggggAACCCCAAAIIIIAAAggg4AWSHgAtV66cgsWLRo0aleM1jBs3Trt27fL1Z5xxRo7jQYUFT6dMmeJ327ZtK1ssiYIAAggggAACCCCAAAIIIFByBBaskL78UVq+PvOZfl6XUbdwZWYdWwgggAACCOQmkPQAqHUmGNY+ffp0/eUvfwkHPC2jc8iQIb6/tvBRrFXid+zYoXPPPVebNm3ybW2bggACCCCAAAIIIIAAAgggULIEbnxWOuMR6cmPMp9r1NSMulsnZdaxhQACCCCAQG4CRRIAvf3229WwYUPfr3/84x+qU6eObLj7UUcdpTVr1vj6Bx54QK1bt87S9xUrVmjEiBE69thj9c033/hj+++/vwYOHJilHTsIIIAAAggggAACCCCAAAIIIIAAAggggIAJlC8Khpo1a8pWej/ppJP0yy+/aNu2bYpcHf7qq6/WoEGDcnTNhs5v2LAhXF+7dm09//zzqlatWriODQQQQAABBBBAAAEEEEAAgZIh0OtwqXXj6M9yUP3o9dQigAACCCCQXaBIAqDWicMOO0zz58+XzQP67rvvau3atTr++ON1yimn+MBo9o7avq30HgRAO3furLFjx4bnE43WnjoEEEAAAQQQQAABBBBAAIHiK3DrqcW37/QcAQQQQCB1BIosAGoElgl62223+a94SC655BLfrFu3bjruuOPiOYU2CCCAAAIIIIAAAggggAACCCCAAAIIIFCKBYo0AJqo+1133ZXoKbRHAAEEEEAAASeQHgpp02+hmBaVy5dRFfdFQQABBBBAAAEEEEAAAQRKmkCxCoCWNHyeBwEEEEAAgWQJpLvY549bYgdAG1YVAdBkvQzugwACpVrg3jel2cuiEzSsIY27OPoxahFAAAEEEEAg/wIEQPNvx5kIIIAAAggggAACCCCAQEICu/dIu9xXtBKrPlpb6hBAAAEEEEAgfgECoPFb0RIBBBBAAIFiK1DWjW5vVDVjiPuGnSH9lp7xKPUrS+XdweoVGP5ebF8uHUcAgWIlUNtl3DdwmZ47d0mbd2Z0vVpFqVolqX71YvUodBYBBBBAAIFiI0AAtNi8KjqKAAIIIIBA/gXKlimjfatlBDm3u/Sj39IyrtWgallVKkfwM/+ynIkAAggkJvDnEzPaf7RIGvpexnbvdtIlHRO7Dq0RQAABBBBAIH6BsvE3pSUCCCCAAAIIIIAAAggggAACCCCAAAIIIFC8BAiAFq/3RW8RQAABBBBAAAEEEEAAAQQQQAABBBBAIAEBAqAJYNEUAQQQQAABBBBAAAEEcgpsd9NqfL08s/77tdKqzZn7bCGAAAIIIIAAAkUpwBygRanPvRFAAAEEEEAAAQQQKOYCHyyURn+SuaCPPc78VdLlz0inHiZde6xUkZ86ivlbpvsIIIAAAggUbwEyQIv3+6P3CCCAAAIIIIAAAggUmcDr30gPvZ81+Bl0JhSS3vxWuusNya29RkEAAQSKncB1112nDh06qFu3bkpL+30FyQSfYuzYsf4aDz/8cIJnRm++Z88e/fDDD9EPUosAAjEFCIDGpOEAAggggAACCCCAAAIIxBL4ab3L/Jwe62hm/Te/SC99mbnPFgIIlD6B9HRp0Upp5vfSj2uKx/OvXLlSY8aM0ezZszVt2jRNnjw5Xx1fsWKFv8bPP/+cr/MjT5o1a5bat2+vF154IbKabQQQiEOAAGgcSDRBAAEEEEAAAQQQQACBrAKvfiVZlmc85dWvpT0uAEJBAIHSJbBzl/TI21K7O6UThkq9h0vH/lU65n7puc/i/x5SFGpPP/20LNuyT58+/vajRo0qim5kuedTTz2lOXPmZKljBwEE4hMgABqfE60QQAABBBBAAAEEEEAgQuCriEWPIqqjbm79TVpaTLK+oj4AlQggkLDA5h3SuY9mBEDXb8t6+rJ10m0uifH/JqbuL0fGjx/vOz106FA1atRIH3/8sebPn5/1QdhDAIFiI0AAtNi8KjqKAAIIIIAAAggggEDqCGzYnlhf1ifYPrGr0xoBBFJN4KZnpa+X5d6rKS6T/OG3cm9TFEenT5+uRYsWqUWLFmrWrFk4C3T06NEF3h0bIv/OO+/44fZTp07V2rVrc9zDMlHnzZun9evd3COurF692u/bJwUBBOITIAAanxOtEEAAAQQQQAABBBBAIEKgZuWInTg2a1WJoxFNEECgRAjYXJ/vzY3vUUZPldZuia9tsloF2Z+9e/f2t/zTn/7kP21Y/PbtBfPbnA0bNuiGG27QAQccoFNOOUX9+vVTz549fbbpbbfdpt9+c6nzv5d169bp8MMP16RJk3zNo48+6vf/8Y9/BE34RACBPATK53GcwwgggAACCCCAAAIIIIBADoG2TaQPF+WojlpRpYLUbJ+oh6hEAIEUF7AFjB56M7FOfrIw/vZpu6WBz0mHuu8p8ZZ61aWre8TbOrF2W7du1UsvveRPuuyyy/xnly5dfDaoZYU+//zzuvLKKxO7aLbWITeB8rnnnivL+GzcuLEGDBigli1b+iH2w4cP10MPPaQZM2b442XKlFGNGjVk9a+++qo++eQTnXbaaerVq5dfECnbpdlFAIEYAgRAY8BQjQACCCCAAAIIIIAAArEFzjoi/gDoHw+XKpaLfS2OIIBA6grscYudjXy/cPs3db5kX/GWZg0KLwBqwc9t27apY8eOat26dbhLl19+uQYNGiRbDGlvA6AjR470wU0bXv/ZZ5+pQQP3QK6cddZZsqBrp06d9NFHH2nixInq27evqlSpohtvvFFLlizxAdCuXbv6/XDn2EAAgTwFGAKfJxENEEAAAQQQQAABBBBAILtAq4bSBUdlr82536y+dHHHnPXUIIAAAqkoMG7cON8tC3hGlksvvVRly5bV7NmzNXPmzMhDCW8Hc4kOHjw4HPwMLtKkSRPdd999fvfhhx8OqvlEAIG9FCADdC8BOR0BBBBAAAEEEEAAgdIq0LeLVK2S9PT/pF17cip0Pli6tadU2Q2BpyCAQPEUKO/SpsZemVjf//2lZAscxVv6nSB1cN8v4i3VE5yDON7rLliwwGdkVqpUSRdccEGW0ywwacPO3333XVkA8+ijj85yPN6d3bt3a/Hixb75SSedFPW0oN7a2QJI5cqVi9qOSgQQiF+AAGj8VrREAAEEEEAAAQQQQACBbALntZdOaCFNcglRb87LOGhZn/27S60bZWvMLgIIFDsBNwWlTnFTXiRSWrj/9t/6Wkp3w+fzKnWqSbecIlV1v0wp6jJhwgTfBQs62qJD2cvmzZt91QsvvCDLzqxdu3b2JnnuL126VLt27VL16tVVr169qO0t2FqhQgWlpaXpp59+UtOmTaO2oxIBBOIXYAh8/Fa0RAABBBBAAAEEEEAAgSgC9d2CJMcfknnAAp8EPzM92EKgtAk0c1NkXNU9vqe+xy20ngrBT8vMtFXerdSsWVO2n/2ratWqKl++vF8J/qmnnorvAbO1ssCmFbu2LYYUrQT3tWNB+2jtqEMAgfgFCIDGb0VLBBBAAAEEEEAAAQQQQAABBBCIQ+DOM6XzO8du6BJLZW36pMgcwW+99ZZWrVqlOnXqaOXKlVq9enXUr379+vmHCubxjP2E0Y8ceOCBPqi5c+dOf/1orZYtWxYOju6zzz7RmlCHAAIJChAATRCM5ggggAACCCCAAAIIIIAAAskRSHNzy/62O/qXHaOkrkA5F214+ELpKRcv7NYqcy7gWlWkPx7ppsy4Vfo/N0dwqpTx48f7rpx33nmqWLFizG4FK8DbfKG2UnuixebzDFaXt6H00UpQbyvRV66cOeGpLcJkxYboUxBAIDEB5gBNzIvWCCCAAAIIIIAAAggggAACSRK46WVp6droN2vphlmP6BP9GLWpI9DzMMm+rPy2S6qUgouiWbbnm2++6ft4ySWX+M9Yfxx55JFq166dvv76a40aNUrdu3eP1TRmva3yfvbZZ2vIkCE64YQT1LZt23DbWbNmadiwYX5/wIAB4XrbqFLFRY9dsXlBKQggkJgAGaCJedEaAQQQQAABBBBAAAEEEEAAAQTyIZCKwU97jGeeecbPyWmLDXXt2jXPJwuyQCdPnhxzGHtuF+ndu7f69OmjNWvWqHPnzurbt6+GDh2qSy+91N9/06ZNGj58uC666KIsl2nWrJnft2xVC8Lec889WY6zgwACsQUIgMa24QgCCCCAAAIIIIAAAggggEARCuxXR2paX6rnVgoPSn23bXX7Jb4Ad3AJPhHIIhAMf7/44ouz1MfascBkpUqV/GruTz75ZKxmuda/9NJLPoPUVoOfOHGiBg0apBdffFE27H3cuHG68cYbc5x/+eWX+8CpLcT0zTffaOrUqTnaUIEAAtEFGAIf3YVaBBBAAAEEEEAAAQQQQKBQBFZvlr74IfPSc5ZLP7rEroPqZdaxlSEw6KSMz8lfS6OnZ2xf0EE6vQ1CCBScwPz58xO6mC2UZIsYxVPuvfde2Ve0cu2118q+bNElG9ZuQ+FtpflYxVaEt8BpWlqaP2ffffeN1ZR6BBDIJkAANBsIuwgggAACCCCAAAIIIIBAYQikh6Sn/ye99KVbxCQ98w5zVkj9npf+0Fq6oZubI5Gf0jJx2EKgFAhYIDORYKYt0mSryVMQQCB+AYbAx29FSwQQQAABBBBAAAEEEEAg3wKPfSQ9Pytr8DPyYu99J907JfbxyLZsI4AAAggggED8AgRA47eiJQIIIIAAAggggAACCCCQL4EZP0pvzcv71K/ccPh/z8m7HS0QQAABBBBAIH4BAqDxW9ESAQQQQAABBBBAAAEEEMiXwGtuDst4SyJt470m7RBAAAEEECjNAgRAS/Pb59kRQAABBBBAAAEEEECg0AVCbu7PuW6ez3jLmq3SKrdQEgUBBBBAAAEECkaAAGjBOHIVBBBAAAEEEEAAAQQQQCCqwPZd0u6IRY+iNspWuWlHtgp2EUAAAQQQQCDfAgRA803HiQgggAACCCCAAAIIIIBA3gLVKkoVy+XdLrJFnaqRe2wjgAACCCCAwN4IEADdGz3ORQABBBBAAAEEEEAAAQTiEDhivzga/d5k35pSgxrxt6clAggggAACCOQuQAA0dx+OIoAAAggggAACCCCAAAJ7LdDnyPgv0ad9/G1piQACCCCAAAJ5CxAAzduIFggggAACCCCAAAIIIIDAXglYBmg8QdBjmkqnHrZXt+JkBBBAAAEEEMgmUD7bPrsIIIAAAgggUMIF9rjViIOyx5YmVplgl08EEEAAgUIUuKqrVLea9NQX0s7dWW9Uzn0rPusI6cpj3Hdlvi1nxWEPAQQQQACBvRQgALqXgJyOAAIIIIBAcRFYtzNdq7aFlBaxEvHCDSHVrZSuxtXLqEJZfuIuLu+SfiKAQPEVOLud1LOlNOFz6e35Gc/R4QDpxh7M+1l83yo9RwABBBBIdQGGwKf6G6J/CCCAAAIIFIDAsi3pWrYla/AzuOz630JauCHdZSNFpIYGB/lEAAEEEChwgVpVpHYRiyK1akTws8CRuSACCCCAAAIRAgRAIzDYRAABBBBAoCQKrNmRrnU7cw9u7nJZod9vTlfID4kviQo8EwIIIIAAAggggAACCJRWAYbAl9Y3z3MjgAACCJQKgXQX0Fzphr3v3iMt+CX2EPcGNUNqUFta7wKl9arEblcq0HhIBBBAAAEEEEAAAQQQKFECBEBL1OvkYRBAAAEEEMgqsHWXZIsepbuvFetjD/yoXCHdBUBD2phmAdCs12APAQQQQAABBBBAAAEEECjOAgRAi/Pbo+8IIIAAAgjkIZAWueR7Hm3t8G8uU5SCAAIIJCIwZro0famUFvH944OF0syfpIrup40nL0rkarRFAAEEEEAAAQQKXoAAaMGbckUEEEAAAQRSRqDM76PZy5eTOh6SEZ1Y+EtZbdqecaDtgXtUuaJUuUJGl1kIPmVeHR1BoNgIbNohrd6Stbs7XPa5fVXip42sMOwhgAACCCCAQJEI8L8kRcLOTRFAAAEEEEiOQJXyFugMyQKbtatl3LNCxL/+NatKVStl9qVKud8jpplVbCGAAAK5CpRzs2tUiDHDRgX3yxcKAggggAACCCBQ1AIRPwIVdVe4PwIIIIAAAggUtEBVFwCt4v6137E7vivXq0wAND4pWiGAQCAwsKdkXxQEEEAAAQQQQCBVBWL8rjZVu0u/EEAAAQQQQCBRgf2rl1U8Yc06lcqoesV4WibaA9ojgAACCCCAAAIIIIAAAkUnQAZo0dlzZwQQQAABBJIiUK1CGR1Us6x+3JzuBsNHL7Vd8POAGgQ/o+tQm5dAKBRSbutt2RQMZYMJafO6GMcRQACBCIFtv0mvfCVN+Taz8pkZ0sbt0tlHStXcPNYUBBBAAAEE8hIgAJqXEMcRQAABBBAoAQIW4Dy0bln9uiNrCLSq+z+Bpi44WssdpyCQX4GtbrGbJZvSY55+kAuu12F6hZg+HEAAgegCP6yV7poird2a9bgtvPXsTOm9BdIDp0sH1s16nD0EEEAAAQSyCzAEPrsI+wgggAACCJRQgYpugaP93HB4vy7S78/YuBrBzxL6unksBBBAoFgLbHRBzjvfyBn8jHyoX7e4Nv+RNu+MrGUbAQQQQACBnAJkgOY0oQYBBBBAAAEEEEAgAQEXW1e13/+vcrtbcCvIMw7qytsYeEqJFVi4WrJAVLRiK8Qf0zTaEeoQyF1gksvwXLct9zZ2dI3LDn1xtnR117zb0gIBBBBAoPQKEAAtve+eJ0cAAQQQQAABBApEoKqbZ7ZFnXL+Wt+u26NdbjS8hTyDugK5CRdJWYHFa6R5K6N3rzwB0Ogw1OYqkO5+izJ1Ya5Nshz8wLW96hj3fYfftWRxYQcBBBBAIFOAIfCZFmwhgAACCCCAAAIIIIAAAggUsYBlfm5xix/FWza4BZFsXlAKAggggAACsQTIAI0lQz0CCCCAAAIIIIAAAgjkKXDU/lLzfTKGIn/2fUbzg9yiNEfsJzH7QZ58NIgisCf2mmpRWmdU5eecmBfjAAIIIIBAiRMgA7TEvVIeCAEEEEAAAQQQQACB5AnsW0tq1VA6oE7mPetUzahr0SCzji0E4hWoV02qmECqTpUKUm33d46CQEELXHfdderQoYO6deumtLS0gr58sbne4sWLC6yvAwcO9KbvvPNOgV0z3guNHTvW3/vhhx+O9xTalSABAqAl6GXyKAgggAACCCCAAAIIIIBAcReo4KYU7nJw/E/RtalkC25RUltgzTpp0VI3XcHm1O5n0LuVK1dqzJgxmj17tqZNm6bJkycHh0rN5549e3THHXeoffv2BfbMS5Ys8abr168vsGvGe6EVK1b4e//888/xnkK7EiTAPxMl6GXyKAgggAACCCCAAAIIIIBASRC4tKPLAs1YWy3Xx6nsMkUvdm0pqSng4mca87R05AnSwUdJ7XtKTdpK3c6U/pP8BMCEkJ5++mlZALBPnz7+vFGjRiV0fklovHHjRj344IOlOvu1JLxHniFDgAAofxMQQAABBBBAAAEEEEAAAQRSSmA/N6XCnSfnHgSt5IKfd50i2TQMlNQT2O4Wpup9mTTwHmnx7/MDB72c/Y104bXSzXcHNan3OX78eN+poUOHqlGjRvr44481f/781OsoPUIAgbgEEphZJa7r0QgBBBBAAAEEEEAAAQQQQACBvRbo7IbBP3aeNP5zacaPUuj3K5Zxn3bsii5u7lm34BYlNQUGDJKmTs+9b2OfkQ50C6bd1C/3dsk+On36dC1atEgtWrRQs2bNfBboY489ptGjR2vEiBH57s6XX36puXPn6v/Zuw8Auarqj+O/2WR303slkAIJIUBooXckKiAoRQULCgiIKFhARUFURBTxr1iwgr3QlaI0IYh0QiC0UNJI72Wzye5my/zPeW/fzuzu7OybsNmdnflenZ039915793PLJOdM+fe27t3bx188MEaO3asfCi4D7cfOXKkhg0bFhx7zZo1WrlypcaMGaM+ffrokUceUUNDg4499liVl5c3O79nab744ovyeTp33nln7bPPPho6dGizNi0f+FDw119/XT4c3dtOmjRJu+22m8rKypqa+jXNnx9GrpPJpF599dVg35QpU1RSEi+XrrKyUv/5z3+C5x1++OFN/Ws6SYaN7dWfDKeiqsgECIBu5xd8wYIF+u53vxuc5YILLggm3G3rlOvXr9eXv/zlYLe/sfbs+c5fHp/bYqedbGlOCgIIIIAAAggggAACCCDQzQTGWxznqhOlW54PA6F++ecdLp22TzfrSJFd7gsvSzfHnDLzmuulT54hDc6jTN4o+/OUU04JXrmPfOQj8gCoD4v3IeEelMylVFRU6KSTTgrmEk1/nscIJk+erAV+88EAAEAASURBVC9+8Yu6+uqrdfnllwe7fbGer3/96/Jh93/84x/19NNPB/XDhw+Xf8b3IKgPz7/mmmt01VVXqa6urumwPXr0CI7zjW98o1VMYcmSJTr33HP1wAMPNLWPNjzQ6/0+8sgjg6rvfOc7wfn9QW1trfbcc8+gftOmTerXr1+w3dYPb+NmDz30UNPw+UQiIc+mbats7/60dV7qi0fgnUfYisdqm3paVVWlN954I3iu/8fub5h9+9qyhhmKv2lFbTPszqnK3zz8TfPOO+/Ugw8+mNNzaYwAAggggECxCzRYpsPm2rYVym1eurIenoNEQQABBHITuOrf0qzFUn1D6nk3z5TueEEa0d/mS/xoqp6tlED6fKDp26kWbG0vAUs81A2/y+3o/w6T/mI9yYfKX3KlzRM6NVbzoNGQQdLHPhi/fS4tPWvx1ltvDZ7yyU/aGH4rhxxySJAN6lmhf//73/WpT30qqI/zw7MnP/7xjwfBz6lTp+ozn/mMhgwZon//+99BRmn//vYffhvlRz/6UZDZ6cFHjy1MmzatKQP0wx/+cPB5f8SIEbrkkkvkmZmeBeoZqh4U9YzN22+/venInlm51157yROvjj76aL3nPe8JsltnzJihe++9V/PmzdNpp52mRYsWBRmqPvfpjjvuGARTPagarZzeMgO16QSNG97fT3ziE/rXv/6lvffeO+jvgAED9M9//lOXXXZZ0/W3fN727k/L8/G4+AQIgHbia75q1SrdcMMN+spXvrLdz+pv2n/9619bfeOz3U/MCRBAAAEEECgAgRpbtGHuxrToRIs+7dgvoeG9CYC2YOEhAgjEEKixRK2qFl+w1Nnbjd+qW9THOBxNENjuAr6Q0deu3r6nufUuyW9xy667bL8AqAc/N2/erAMPPDAIKkbXdNZZZzVlZeYSAP3BD36ge+65RwcccIAeffTRpuzR008/Xfvuu2+Q/Rmdo+W9BzR/8pOf6OKLLw52VVdXB/f3339/EPz0uUl9+LsPn4+KB233339/3XHHHUEylAc6vdx0001B8NODsD4s3YOaXjzw+K1vfUs77LCDfOi9Z4eefPLJOuaYY4KAqWeletvPf/7zQfv2fvz4xz8Ogp2+cvz//ve/pv56RqhnmWbKAu2M/rR33ewvfIF4EzcUvsN276Gne3vxN75nn312u5+PEyCAAAIIIIAAAggggED+CQzoJQ2xAWGZboNyG1Wbf53jihAoAAEPFHrxgGd68axGn/vy+eef13PPPZe+K+v2P/4RzgXgw9VbDp2/6KKLgszStg4wevRoeZuo9OplbyBWoiCiBy7Tg5++z+f0/OhHw1RyzyCNis8N6tPz+UjRKPgZ7fNjHHroocFDn5P0nZS77747ePoVV1zRqr8+rN+zX1uWfO5Py2vlcfcVIAO0k147T/n2SX89Dfzaa6/NOhQ+2yX5NzI+UbFnk/qEyP4NyqBBlv+fVryNT2rsxdPPfR5SL+PGjWtzsmI/nn/L5ccaPHhw0L7lD5+EecuWLcEbqvcnKj4Zs89D4tflQ+99AmWfzLnlm6q397R7T7n3yZ39zdv/8fBr9DfjFStWBIf0OUszzX/q53n77beDNhMmTAju+YEAAggggMD2EOhpXxEP6xV+ebmhJqm6xpU3hti6AyX2pWYvhr9vD3aOiUBRCHw1TMYqir7SycIQ8ETBn16TW1/utikm//Pf+M/5xOnS/nvHbz8w9XE0/pNitPSFgZ588slgmPYZZ9jEpGnFP3+/+93vDjIkfc0Oz+hsr/jn45deekmeEHXEEUe0au6fmY866qhgwaVWO63C5weNkqnS90er0fvzPau0ZfHAqRfvT1R8ASW/RcWvzWMFPg2fzzHqQ+C9pM8nGrXN5X727NlB80z99blDPdDqQ+7TSz73J/062e7eAgRAO/H1829u/JsiDzb6BMo+/0Xc4pMI+zc1d911V7D6W/Q8/wbK35g9BT9asc0nSfb5Nbz4m5p/U+XFU9lbfuMU7LAfvqqcD88/6KCD9MMf/jCqbrr34OOnP/1prV27NriOKADqb5jf/va3m94soyd4gPLKK6/UxIkTo6rg3jNgf/Ob3wRzlNx3332K3ugGDhwYXJuvNOffYqW/MUcHcLtLL71Ue+yxRzBXSlTPPQIIIIBAPIGtNuxy9lLJh19GZaZ9r7T/WGnkdvogEZ2nu92XliS0U/8wALq5rt4+DIQ92LFfiXrYPgoCCCCAAALFImAfOXVOjnPTHrBP/ABof1tP53u29s/2Cmrm8jr9/ve/D5r75+ho0Z/05/tiRl5uvvnmYE7MlslI6W192wOQPnenz9PZ1tyZnqjUVvFV3VsWTyrypCcv5513XsvdzR57olJNTU3TuT2h6Prrr9fDDz8cBD63bt3a1D5TElLTzpgbPn+oX58nO0Ur2rd8qs8rml7yuT/p18l29xcgANqJr6EvfuTzf3oQzzNBjz76aB188MHtXoFnSHr6+KxZs4LsS5+M2LMkFy5cqNtuu01/+9vfgkCiT3bs3w75XB2+OpwHTD1A+rnPfS44RxQgzXTC9773vUFQcebMmUGGZsssUM/U9OCnBzZ322234BBz5swJju1vmv6tld/8/M8884x8Do/zzz8/WDXOv7VqWW655Rb5CnR+PH9D9jb+5u7DDXzRpkwBUD+ml+OPP77l4XiMAAIIINCOwNIN0j/sC/nN9nfugN6pxm/Z38+vLJcOsL+9j5kkex9P7WMLAQQQQAABBBDYFoGpu9sQ8jOkP9zc/rOvvDQ/gp+e+eiLFnvxhJ9MmZCeUOTzcPrISE88am9ezOgzeBQ4zaTh63e0VTIFTT0+EBVfkT46R1TX1r1/pvcYhJ/Pn+MLKvlcob4wkscQvvSlLykavt7WMdqr7907/CPTA8ieROXxiJaltLS0WVU+96fZhfKg2wsQAO3kl9AzLE888cQg5dsnQ/Y3WE8Dz1Z88mIPfvqkxJ5qHwUnjzzyyCAY6IFGn/jYV5F73/veJ59s2IfGRwFQD5i2V/yYnorukxT7hMgtn+PZo15OOOGE4N7fpPybIw9+nnPOOTr77LODev8xffr04PyeUeptfvnLXzbtizY8+OkTOUfn8SCof/Pzu9/9Lgig+nb6t2n+D8xjjz0WvFFnCo5Gx+UeAQQQQKC1wBr7u/qWWVKtLWLQVnnubQt+2s5jdm2rBfUIIIAAAggggEB8gf/7trR6rfSvh9p+zufPlz5zVtv7O3OPf572adn8s7GPTGwrsOgJRv5Z1z+btxcA9YQfz6z0oKlPKddyvk7vXzRlXdy++vV5dqVngfoCR76QUpzin9k9+Onzg954443BSu/pz4uuwwOX21o8Ecunw/NMUJ+Wr2W2px83mtYuOkc+9ye6Ru4LQ6B1OL4w+pXXvfA3TE+BX716dTAUvr2L9WHvXs4999ym4Gf0HH+D8QCkF0/DfyclCm56BmZ68ZT9//73v8Gcnp4p6uWFF14Isk79jTcaYp/+nPe///3BPxivvPKKXn311fRdwbZPzPzBD36wqd6/2fJ/DPxbKP+2yIfkp5cZM2YEwVafR6S9gHH689hGAAEEEJAefD178DMyetaCoCs3RY+4RwABBBBAAAEEtl3APuLp5t9Iv/6htPceqeN4UuCRh0h3/Un67tdT9V295ck4XnxV9LaCn74/WgHeh7dnmn/T20TFg58+UtJLtLhStM/vPSjq08TlWqLh+Z4slal4gHPKlCnyFeG9+MJGL7/8crDtU9hFmZpBhf3w9UDefPPN4GF65muUwZlLUNSzSr3cfvvtwX36D5/a74knnkivCrY7qz+tTkxFUQkQAO2Cl9uHwn/1q18NzuzfMj311FNtXoW/+fi8HV4OPPDAjO2ies+q9ODhthYfju/fvvgbuX9jExXPvPRvrA455JCmAKwPv/fikyv7pM4eEE2/+UTK/m2Xl5bf8HidD+HPNJlzFISNMk69rReGv4cO/EQAAQRyFVi3WVq8Pv6zZi+J35aWCCCAAAIIIIBANgGfWudjlvfyxL8s2Pea9IZ99F09R/r336Vjj8z2zM7d54FIn6bOy5lnnpn15J5x6Yv4esk02rHlk6+66qqgyoerR+fwCs/g/NjHPhYMp2/5nPYef/Ob3wya+Pod/nk9vfjnbx/O7p/rx48fH+zyofvRHJ+eXJRe/LO+JzD5qEwv/jgq0RoiHpdYunRpVJ313hO0PHDqK7v7NUTFR5F+7WtfC6bWi+qi+87qT3Q+7otTgABoF73uHrQ86aSTgrP7UHj/JiRT8bRxD2r6NzS+UFCm4lmgvvqbvyn5G/e2Fn9DjDI8H3ooNU4hCkZGwUk/fhSU9W+RfCh7ppsHQb1keqP04fyZig/r9wCxL44UPc/75EP8Pds0+jYp03OpQwABBBBoLbA8nKu/9Y42anJt38ZhqEYAAQQQQAABBJoJ9O0jjRktW5CnWXVePPjzn/8cfJ72dSkOO+ywdq8pygL9xz/+0e5ncJ9q7uqrrw6Gn/t0eJMmTQqmn/Oh4s8++6x2390mTLUSBSjbPbk1OProo3XBBRcEQUufv/P000/Xd7/7XZ122mnB4k0eX/Dp93wNEi++KJG38eJrknz84x8PhvBfeOGFmjp1apCVGX3Wjj6He1sfqRl9dvfAr7fx6QGyFZ+Wz4O9vvizX8NnPvMZeRD48MMP1y9+8YtWCyX7sTqrP9mum32FL0AAtAtf42govH/z4wsYZSrRm6AHQdMnB05v6/uizE8PhL6TEgU5o2Hwfm2+MJLPx+kZoC2Lvwl6P7LdojfS9Oe2NaTA32CjOT6jwGuU/enB2Xfav/RrYBsBBBAoBgFf+T2Xkmv7XI5NWwQQQAABBBBAIB8FouHvHhiMUzxz0z+71tbWBvNptvecyy+/XD61nWda+voWnqXpn709AOrTwHnxhZdyKZ59+te//jUIUN56663Bwsl33nlnEBvwuUnvu+++ILkoOqYHH6N5QP15Hpj0dUN8/RBPbPrxj38cNP3nP//ZLPbg65Z4ENSn8POFlDJNcRedI7r/8pe/HAQ9/bHPleoZnr6Isi8cFSWCRW2j+87qT3Q+7otPgEWQuvA193Tyyy67LEhP9yBfNO9F+iX5vJge9PPFhnzeDp87s2VJz/pMXzioZbs4j33Yun8D5RmY/gblw9s98OqTK0fBWD+OD2H34n2IvkkKKjrgh/9D4KvP+Xwqnj4fpeiz+nsH4HIIBBAoOoEBvXLrcq7tczs6rQtVwNdL2No4C0+tBd1r7bGNelR1bdjjUvt+tgdfuxfqy0+/EEAAgW4v4J9/cyk+dVz6UPE4z/XAX6bgny8A7CX9s7wPFfdbe8UXNPLb2rVr5SMw/br8M71nfLYsHmD1QO+PfvQjzZ07N/h87/OEeiDXi2emZkq68gQlzwr1BaJ8BfdMMYmW5/LH3/jGN3TJJZcEw+D9HB5n8GnwfIoBv4ZMZXv3xwOx0XD7TOenrrAFCIB28et7wAEHBN8CecDPV5JrWTz46fN2zJs3Tw8//HAwIXPLNl7vJf3NK5qsONMbWMvnt3zsAUj/B8DnEvHV571EmaFR22h+z9mzZwert6e/WXsb/8fAh8X7G9ynP/3pYGX66Lnt3e+xxx4aN25csBqeZ5963/3N0usoCCCAAAK5Cew0xIZUWeDJg1MbtoTPrbYA1ZaacLvU/hLwgFXvUruVSbsMz+34tEbABRbbZ7ebn48sUqNRHmmsev9U+ztlVLSfewQQQAABBIpH4JRTTpGv1+HzdUYLIkW996nlfMFhL9HaHtG+XO49KOlD7eMU/+yeaZRme88dNSr3f8g9YWq//fZr79Ct9ndGf1qdlIqCF+C7+Dx4iT/72c8GK6D7auuZSrTKu89L4t/UpBefVPjvf7cZpK20XFXd63xovKeq51L8Gx4fou4p8x4InTx5cpAWn36MaOLnyspKXXfddU0TJkdtPM3dM0gXLFgQPD+qj3sfBVyjb4aOO+64uE+lHQIIIIBAmkCZxaIOHi/VWQD0RVvgyG9Pzks0bT+3MNxevlHqZwkAe49JezKbCCCAAAIIIIAAAu9IwIeYe2KPL0yUPnzcP2v7Z/2KigpNnz691Wfud3RSnowAAq0EyABtRdL5FdFQ+C9+8YsZT+4LA/nExj4U3LMpPUDpQ9B93hDP/vTFjzzb0oepR8UDmP6tiafC+5uqD6X3iYh9IaH2Sr9+/YJvpqKFkKJgZMvn+Ru4z/3pmaJnnXVWMFm0D5N/4okntHDhwiD704f4+6JGuRaf7/PXv/51sNiSp9n7PwgUBBBAAIFtEzhkZ2nBWunxeW0/34cnn7q35EOVKQjkKlBuf1Hu0LhW4/KKpA2h8wHwSavz+zDDONjgBwIIIIAAAkUm4EPB77333mB0pU975/NpNtjcMT6k3MsRRxwhn3eTggAC21eAAOj29Y19dE9B9wmRfSh8puKrpvmb4k033RRkZnobDzb6sHdfZc1vLcsVV1wRrDbnQVCfV8SDknECoH4cD3p6ADRb8NGHwXtWqmdpetDzlltuaboEnz/k/PPP18EHH9xUl8uGB2/9uU8++WSwWlz//v1zeTptEUAAAQTSBEosBnXqPtLrK6WVFdLqyqSqasPA1OiBSQ3qndCJe0qjGwNYaU9lE4FYAqNs3YYzDwyb/uTRcO5P/72L6mIdhEYIIIAAAggUoMDAgQODDFBP8LnnnnuCz+U+H6d//veFhn0k57YkDRUgFV1CYLsKEADdrrwK5q783//+F+ssvlKa39oqJ598svzmK7P7wkeeSp9pcuPo+R5U9aCpB0A9WOpvvHGLPzfOdQ8ZMiQIsnoWqs9r4kPiR48e3ebEyD7hsd/ilGjRpbYyUOMcgzYIIIAAAqFAH5vf8+qTbL5PGwp/3t+kKhvy7uXTh0uHTAi3+YkAAggggAACCCDQ8QI+ytIXBPIbBQEEukaAAGjXuL+js3oWZ9xMTj+RZ1Nu7+LBSl+sqaPK+vXrg+zPESNGvKPJoDvqejgOAgggUCgCPsQ9zP0Me9TXAqMUBBBAAAEEEEAAAQQQQKCQBQiAFvKr28365tmjPgH05s2bdcMNNwRzm5522mmKVrSP053bbrtNjz/+eKumy5Ytk2errlu3rtU+KhBAAIH2BDyT3qciaVl8kTnPes91sbmWx+ExAggUr8CNN96ol19+uRVAdXV1MHpn48bGdO1WLahAAAEEEEAAAQQQiCtAADSuFO22u4BPAn322Wc3nWfq1Kn60Ic+1PQ4zoavpHf//fdnbNq7d++M9VQigAAC7Qls2bKlzfcWn6PYA6QUBBBAYFsEZs2aFSxqmem5PtURAdBMMt277q6XpIVtfCc/oJd09rZNod+9Ubh6BBBAAAEEtrMAAdDtDMzh4wuMGjVKu+22mzZt2qRp06bpvPPOCxZhin8EWiKAAAIIIIAAAgggkN8CNXXhQmGZrrLMpimhIIAAAggggEDHCxAA7XhTjriNAj4x9G9/+9ttfHb4tAsuuEBnnHFGq2NcdNFFmjFjRqt6KhBAAIE4AiNHjtTdd9/dqunMmTN1zjnnqLa2ttU+KhBAAIE4Apdffrk+//nPt2p6+umna/78+a3qqej+AuX2CaxXqVTfEC5M5z3qWWI3C356PaW5wJ+fkVZukhalZc3+53XpjZXSDrbG60cPaN6eRwgggAACCGQSIACaSYW6bivgQQq/tSzl5eXBnKIt63mMAAIIxBEoKyvT5MmTWzVdvny5tm7d2qqeCgQQQCCuwJgxYzI29TnQ6+osVZBScAIf2Cvs0msrpHsap389aLx0+C4F19UO6dBTC6R5a5of6nULfvptsv3ZTwC0uQ2PEEAAAQQyCxAAzexCLQIIIIAAAgUlUNeQ1NwNlm5kJSlLNWosy7Y0qMyyaob2Tmh471R9tJ97BBBAAAEEEEAAAQQQQKC7CxAA7e6vYA7X78M3/TZ9+vRmw8R9eHhVVZWuvfZaDR06NDhiprocThWr6bnnnhu0++lPf6o+ffrEeg6NEEAAAQS2XaCqvvVzay0m6vV+T0EAAQQQQCDfBC6d3vacqX3K8u1quR4EEEAAgXwVIACar6/MdriuNWvW6I033pCvrp5e3nzzTfkKx+nDrDLVpT+nI7b9WrzU12f4RN4RJ+AYCCCAAAIIbKPAhi3SP2aHT66uL7Gs2bC8YHP0JWzz4AnSlFGNldwhgAACCGw3gZ2HbbdDc2AEEEAAgSISIABaRC92W139wAc+EMxhRxZmW0LUI4AAAt1foGdJQnsPC4e4+2IbUdllQIl2sw+XHtSjpATqLCN2VWX0OKVj63AEZQtTv0Y4TfdVdUmt2uKh4pTXgooGjbDpFfqWpuqansAGAggggAACCCCAAAKdJEAAtJOg8/k0F154YT5fHteGAAIIINBBAiWJ1kGohNVZbJSCwDsSWGlzyS7bHOXJpn6hNtQk5beRfRLaoW9a5P0dnY0nI4AAAggggAACCCCQmwAB0Ny8CrL122+/rYaGBu20007q2TP7r4QPV1+0aFHg0L9/fw0b1nxMih9n8eLFmjt3bjC0fdKkSRo7dqx69LAxg1lK+nHbug4/tl+rlwkTJmQ5GrsQQAABBBB4ZwJD+0qXvCs8xo1PJ7VxSxjUu/DwpHqXWdCYWF4T8NrqBj09L6l7nwiN1lbI/q4Id785N6x71/5JvWv3BguEAtcExwYCCCCAAAIIIIBApwlkj3Z12mVwoq4UOP/884M5QG+//XaNHDmyzUvxAOTVV1+t//znP9phhx3kixellwULFujb3/625s2bl14dBCuvvPJKTZw4sVl9+oMS+yR52WWXadmyZfrWt76lY489Nn13sP3cc8/p0ksv1R577KFf/epXrfZTgQACCCCAQEcJeLJsz8bv7sIQXnhkr4vqO+pc3fk49Q1JLa1M6qWXpb9/v2Vw0+VCvd5fatCUcUkNKU+qtEe6aHfuPdeOAAIIIIAAAggg0F0EWv6l2l2um+vsZAEPfl5zzTVB8NMzNH/+8583C5bOmTNHvqq7Bz+POuooecDzm9/8po477jh5YNSDrNGiR5ku3YdgHn/88cGuBx98MFMT3X///UF91C5jIyoRQAABBBBAoNMENm5Nqj4a+d7OWb3ZehsOT0EAAQQQQAABBBBAoLMFCIB2tng3PF8ymdT3v/99PfDAAxo/fnwQ/Bw+fHhTT3z/9ddfHyykdM455wRZou9+97s1ffp0XX755frsZz+r2traoE3TkzJseGDTA6HPPPOMNmzY0KyFr1L/2GOPqaysLGN2aLPGPEAAAQQQaFPAF++prU/tXhWt6pOqYguB2AJb6sKmk8ZKhxzdENxKejYGORPJprq9Jod1VY3tY5+AhggggAACCCCAAAIIdIAAAdAOQCzkQ3jm57XXXqv77rsvGML+s5/9TEOGDGnW5RdeeEGvvfZaMB/oJz7xiWb7/MH73//+IHD5yiuv6NVXX221P6rw4ffTpk0L5g595JFHourgfsaMGUGA9YgjjlC/fv2a7eMBAggggED7ApXV0hm/kA6/RnptobRidXj74t+kY38g3fJM+8egBQItBew70KD0GCAlpySCW6KssZX9lRnV9Rwc1jVODdrYgDsEEEAAAQQQQAABBDpHgDlAO8e5257FMzuffPLJ4PovueQSDRo0qFVfFi5cGNSNHj1aL730Uqv9XuGLFvkQeF/EyOfwbKuccMIJmjlzZpBteuqppzY1Y/h7EwUbCCCAQM4C9RZ1uvJe6fHXMz91lVVf94A0day0++jMbahFIJNAeeM8qVtqpNeXhnN72rSgYUkmrC7crAgWkUqqnK/eMzEWTN3GqlRXNtnvhL/39OA1T6GwhQACCCCAAAJdJkAAtMvou8eJPfhZXl6umpoaefbnL37xi1Yruvuq715efvllXXzxxVk7tnRp4yehNlodeeSR6tu3b5BR6m3HjBmjlStX6sUXXwwyTPfff/82nkk1AggggEBbAn95Vpqd/e1XdRao+M590u/PlHqVtnUk6hFoLjCwPKGlm6OIZ/N9mR55e0rhCSzfKD1oX7CsqEj1ba5lmd/wmHTELtK+O6Xq2UIgV4F7X5HWbc78rGE2MOyEtnMrMj+JWgQQQACBohQgAFqUL3v8Tk+dOjVYzOjTn/50EJS8+eab9bGPfSzjAfbdd18ddthhGfdFlbvuumu0mfHeg62+Avzdd98dZIH6nKJR9ud73/veVsHXjAehEgEEEECgSaDK5vy8/UWpxLKwxu4QVq9dL21uzNTayTI+bfplm6rEPmBukf5tM5Wcuk/T09lAIKtAua3oPrRXQnuMTervl4aTy77voRIlg9Xfvc4i61Z62e/XQLv1LSUAmhW0G+6cZ4HOO2dLTZm/aX2oqg0Do6sqpfdOSdvBJgI5CKy23x/mq84BjKYIIIAAAhkFCIBmZKEyErjiiiuC1d59+PvXv/51/e53vwuCnL4YUlR8VXgvffr00emnnx5Vb/O9D4P3AOijjz4qD4D6/J9eWP19m0l5IgIIFLGAZ35utYVnSizu1L9xCuWKtIWPBvQ1nLQhqs8uJABaxL8u29T1HfslVGNLwftQ53UWqEgv1RYAG9rf/kawrOJx/dN+0dIbsd1tBSptmPtdL2cOfqZ36sUl0g4DbZqNxi9h0vexjQACCCCAAAIIdIYAf4l2hnI3PkePHuHkXr740DHHHBMsRHTNNdcECxVF3fL5Pb3Mnj271ertXl9dXa3zzz9fnkU6a9Ysr8pafI7QcePGacGCBcF8oPPmzdPuu+8e1GV9IjsRQAABBFoJeOaMF0vUC4IPHoDwjM+o7GiL03jdSAtSeYnah4/4mbRVftIHeNdHq/5A0yRQYr9QQ0pLNGtuiWbObZwUtHHvrPk99NybJRpo0dEeHoWnFJTAs29LtWHib7v9enxeu01ogEBGgY8dIH3hGOmoiandx+wa1n1k/1QdWwgggAACCGQTIACaTYd9zQS+8IUvqH///pozZ458KHxUfOj7Pvvso8rKSl133XXBfKHRPr//1a9+FTzHA5qTJ09O39XmtmeBevnRj34U3B933HHBPT8QQAABBHIT6GPDjr34EPjhFuT0W3oYakCvsK5Pediud2P78FHx/vTA54otDXp5bYPSY55z1if19qYGmzM1PSxavE7ec5+b7y/PJrSmMv03K2WyoSqhvz2XaDY/ZGovW91ZwIe/xy0V1XzBEteKds0Fyux7lXIbt9gz7ZOrfecS1JU2/86l+RN5hAACCCCAQJpA2j8jabVsIpBBYMiQIbrooouCPTfddFOQoRk1+9KXvqQBAwboscce01lnnaWf//znQeDzzDPP1B133GHZRglddtllwQJH0XOy3ft8nyX2ad0XWCotLdX06dOzNWcfAggggEAbAruNbGNHG9VTcmzfxmG6dbUHP+dXNGi5Le5jI7tblXXVSb2xvkFbM+1s1brwK3yBkmqbZiFb8UW27vah0uGUoNmasq8bCXhQM5dS0Tj3cC7PoS0CCCCAAAIIINARAvZdGgWB+AI+D+dDDz2k5557Tj4U3rM7fZi8D4P/85//HGRsPvHEE7rllluaDjpp0qRgCPzBBx/cVNfextChQ+XtfRX6ww8/PMg8be857EcAAQQQaC0wZpC095hwFfinF4T704eszlkhLbRFkbzO8/eOZzVdLbPA57J10uP/DTMa55mRLyblpW5JIphPdfc9kuo5sUG7DioJvuQL9xbfz8X2u7M8beXvbALrbZGttyxjcDJB9mxM3WqfZ995cDtuKeOTR1wq2iGAAAIIIIBABwvwZ0gHg+bz4XxBIb+1LA888EDLqmAF9laVjRXRsPSW+z1D9Oqrr1ZdXZ2WLFkSDIkfPXq0PJiZqfzvf//LVN1U17Nn+OsZDYdv2sEGAggggEBOAhcdLV18m7SlMYiXntRYY4vUJBtHLp8+Tdp5WE6HLrjGtTa0fXVVUm9ZsPi732o9UOauxhWjTj2nQV/8TFIbzXRQ4/QBBYcRo0MLLVCcS3nb2hMAzUUsv9v6wkbz1sS7Rp8CdkTjXMPxnkErBBBAAAEEEECg4wRa/2XfccfmSEUq4IHL8ePHa88992wz+Nkezfr164PszxEjRujAAw9srzn7EUAAAQSyCOxkCx1d+wFpWOMq8C2bevzTg59nx0/Ub3mIgnm8aWu46FF7o9vrGhd+2ViTHk4uGIbYHYmC6nGfsLkxCB+3Pe3yW8Czy+OWKaPCORvjtqcdAggggAACCCDQkQJkgHakJsd6RwK+iFJFRYU2b96sG264IcgkPe2004K5QN/RgXkyAggggIB2tWHHv/u49MBr0uWpWUp06M7SeUdI4zMn6xedXE1jYHOQBY0nHBkGN5fOkrY2LvAz7pCkSkptn61A7GVrkS+G1Nsscil9cmyfy7Fp2/kCk0ZYRq/d3liV/dx9bXG1oydlb8NeBBBAAAEEEEBgewoQAN2euhw7J4EVK1bo7LPPbnrO1KlT9aEPfajpMRsIIIAAAu9MwFfRff9e0jX/lNZvCo/1gb0Jfqar+jBdL337Sv0mhtvJl8N7/9l7F6nUgjnDRod1jc1TDYpsa6wFip+y6QLilp2GxG1Ju+4icOKeUg/7YuU1mys3UxncRzptH/vvqYinisjkQh0CCCCAAAIIdK4AAdDO9eZsWQRGjRql3XbbTZs2bdK0adN03nnnBSvAZ3kKuxBAAAEEYgpU22rNN/0tbLzmValmc7h9x+3Sc5b9ub8FQg+aFvNgBdysT08PaSaDRaEWrwnDm+krly9fl1DC/nqqtJXgvfQpLe4Q6DgLaA63qRVWVwYcWX8M6CXtatmClMIS6GkLIZ00VdrLhsP7QmvRvLD9LeB5iGWY77WDBUiZdKuwXnR6gwACCCCAQDcUIADaDV+0Qr3kfv366be//W2hdo9+IZAXAud+QXq4jfXHRtkQ6af+nReXyUVsB4HKLdJXr2p94BteCeu+8jkCoC7Rz4Zol+UQrBlSXtwB0IR13zMA//KcgqBxy9+wpMWJvY1n1p5k7XrmYNvyWDzObwEPhnuJAqATh0v77hjW8RMBBBBAAAEEEOhqAQKgXf0KcH4EEECgEwU2VFim1trMJyxlbr7MMNQWlUDConU79S+xuT0bdNcV4YSg0/9XonqFgc4bLqjXTraYiwf0RvZJqFeQMVpURK066yt7f2R/6SePSHNWNt/9xHxpkgXCLj5a2tGGy1MQQAABBBBAAAEEEOgKAb6H7wp1zokAAgh0kUA/m9dw4AAbtts7dQHlNp+h1w20IAalcAX62Tx8118d3srTAlFnnR3Wve/dhdv3XHs2oCyh8f0T6hHGPJs93YfDe/BzeO+ERlsAlCLVm8lvLLP8hSVSdW1zka110qvLpRsea72veUseIYAAAggggAACCCCw/QQIgG4/W46MAAII5J3AH34mLX1J+vX/pS7t8+eHdc89lKpjq/AEetn8i+faKvB+K7VAeFSOPTasm2ZzgFJSAgPLS1RZUaLHXmn+p9Lz8xNavKJEQ2ycvGeLUqQbn5SebGchpJeWSj97FC0EEEAAAQQQQAABBLpGoPlf9V1zDZwVAQQQQAABBBDIGwHPaLzjRekJC3ZurW8R5EwmNGdFQn96RqqwhaWKvazaJN01O57Cf96Q5q+J15ZWCCCAAAIIIIAAAgh0pAAB0I7U5FgIIIAAAggg0O0F/je3/UDdRgt+/tMCf77ITzGXJ22Oz/ocDNyWggACCCCAAAIIIIBAZwsQAO1scc6HAAIIIIAAAnkrsGWrNHNRvMtbbouKvbU6XttCbbV0Q249W7oxt/a0RgABBBBAAAEEEECgIwQIgHaEIsdAAAEEEEAAgYIQ8CHauWQ0vrWqILq9zZ3okeNfkpkWltrmk/NEBBBAAAEEEEAAAQRiCvSM2Y5mCCCAQF4KXPgV6U+3Zr60MlvdfN2bmfdRiwACCGQS2FiVqbbtOh8KX8xlwtDcej9hWG7taY0AAggggAACCCCAQEcI5Pi9fUeckmMggAACHSeQbeq5Yp+br+OUORICxSPQs0dufe1Z5H9JHbKz1Ks0nplnix41MV5bWiGAAAIIIIAAAggg0JECRf5ne0dSciwEEOgKgRGWTbTLeGmHUamz9+8X1k20egoCCCCQi8DI/rm0lkYNyK19obUe0Es6++B4vTp9P2lkkXvFk+p+rVZtadC8jfVatrm+6eI3bg3r5ls9BQEEEEAAAQQQ6GoBAqBd/QpwfgQQeEcC37Yh8LMflX7/09RhTjsxrHvuoVQdWwgggEAcgbGDpUG947SUEtZsz9Hx2hZyq5P3lj6yv1RXJ61a27ynK21O1dpa6cQ9pTMPar6PR4UjUGWvfYUtILbFXuuobLW4p9f5jYIAAggggAACCHS1AAHQrn4FOD8CCCCAAAII5I1Aif1l9J4pYXCzvYs6eII0pG97rYpj/3DLBH17sbS6RQB0zTppwSJpWLlU4hFjCgIIIIAAAggggAACXSDAIkhdgM4pEUAAAQQQ6GyB+gbpuQXSzc9YRl7aiNSfPmgZWhaY+sC+lvnYp7OvKj/P5wv7nDRV+verkmexpZdohfgDxkpH7JK+p3i3H3lNuuB3UltzMvvv25f/LpXbX52nHlC8ToXc8x36JTSqb0JvRf+BWGfLbT7d3YeQa1HIrzt9QwABBBBAoDsJ8FdJd3q1uFYEEEAAAQS2UeDOmdI375PmWEZeIi0Tzxcx/9sL0rl/lKoYqtqku+sIy1q07M6n5zdVBRuzLctxqw33nWYB0HTH5q2K51G1DXn+6s1tBz/TJa64XdqwJb2G7UIRKLX03vIeCfVI+4+ixLa9zm+U5gL+pcBT9oXUjDdT9TMtU9ofb+F9OIXCFgIIIIAAAh0oQAC0AzE5FAIIIIAAAvko8My8MEiV7drmr5Iu+Vu2FsWzr86CE9/8lwWGLWhcbcHO9OJZjo+b50W32nyXm9L3FOe2Z38u3xCv7xVV0j0WbKcgUMwC/iXAH56WHpsrVdakJGrsvebZt6Ubn5SWbUzVs4UAAggggAACHSNAALRjHDkKAggggAACeStwxW22QI0F9SosYOe3ZNpY5S0WlPK6ass6unuW9ERaRlLedmg7X5gHJ56zQES2stLMrraM2nTLbO0Ldd8LC3PrWa7tczs6rRHIbwGfUuM2+xJgXZZM6CrLqr7N3ov9CwMKAggggAACCHScAAHQjrPkSAgggAACCOSdwCs2ZHvOMqnBgp6Ll4e3evsQHpVVNiTe6z0I6uW2Z8P7Yv25wYIO/5gdr/dvWNbskzaMtZhLegZbHIfNaRlvcdrTBoFCEphpX6xkC35GffXM88cs05yCAAIIIIAAAh0nQAC04yw5EgIIIIAAAnkn8JoFP3Mpry3NpXXhtfUARV1D/H491WKO0PjPLIyWYwbn1o8dcmyf29FpjUB+C7xqXzbFLa+vbL5gXdzn0Q4BBBBAAAEEMgsQAM3sQi0CCCCAAAIFIeDzyuVS0leIz+V5hdJ2RUVuPcm1fW5Hz//W79o9t2s8do/c2tMagUIRqLcvVuJkf0b99faekU5BAAEEEEAAgY4RIADaMY4cBQEEEEAAgbwUmDAst8san2P73I6e/63Le+Z2jbm2z+3o+d969zHScXvFu84Dd5YO3zVeW1ohUGgCPg1JrqUhh2z0XI9NewQQQAABBIpNIMc/84uNh/4i0PkCy1ZIK2xeubbK3pY906NHW3upRwABBJoLHLiLNKSvZR5tbl7f1qMT9m5rT3HUTxyeWz8njcitfSG2vu4j0jwbrvuW3RpaLO5SX2n/ZvWTfKj8zz9ZiL2nTwjEEyi1v936lTdf+T3bMxO2c1DvbC3YhwACCCCAAAK5CBAAzUWLtgh0gsCv/yT93y/aPtESW5xj0MC297MHAQQQSBcos3/pv3yi9LVb0mszb+82Wjpl/8z7iqV2L8toHD1AWh5jKHyJRSimTy4Wmbb7OdgC7L8/W/rABRYIfUkqSQvabHrEgp+TpBvt3zXm/2zbkD3FITB5pPT8onh9HT9UKi+N15ZWCCCAAAIIINC+AEPg2zeiBQIIIIAAAt1a4MzDpLOPzN6FHYdIN50n9SzyDPMe9pfRRUdLCU+/aqecPk3akUV9tGqNdNIZYfAzE9nSt6STPyotXJxpL3UIFI/AweOlXjHST/zLlaMmFo8LPUUAAQQQQKAzBAiAdoYy50AgB4G9bEGJ0z8gHf+u1JN2GBXWeX1ZWaqeLQQQQCCuwHc+GA5BntBiiLcPy/z4odK/L5XGDYt7tMJuN22sdNl77P3WbJIt5u2L5uQ7dR/pkwcVtkPc3l3wZWlzvfSRi8Nb+vOiurJB0lkXtfZMb8s2AoUu4EPgT7P3jmxzB3vw83023dFIy0SnIIAAAggggEDHCcT4DrLjTsaREECgfYHTbKiq396cJ91nQwe97LOnZWb9JNzmJwIIILCtAidbxqLfJth7y+rGg/zuXBvGfeC2HrFwn3fELtIzb0i/ndG8j4uXSYdOkT5kQYw4WaLNn114j158RXrQjMbZVAATp0b9i9JnE011s5+UZs6UHn7Mft+Oitpxj0DxCXjW+FkHS49ZZvTrK+1LgTSC8ZaJf5RNGTGK4GeaCpsIIIAAAgh0jAAZoB3jyFEQQAABBBDoNgI+zDsqZcwxF1E03ddaNuPZv5F+9qBUXdtUHWx4RugDNs/l+34oLVvffF8xPvLgZy7lof/m0pq2CBSmgC9u9P69bLSPZXpG5aDxNtrHvqAi+BmJcI8AAggggEDHCqR9BOrYA3M0BBBAAAEEEECgOwr84F7pkdeyX/niddL5NzGke5llsHnZWpnUwmcbglsqpy1VV7UhzHNbujxsz08EEJDSv4zqyaeyNn8l/IunOSuk2UtTTV5Y0phBG761pHawhQACCCCAQBsCDIFvA4ZqBBBAAAEEECg+gbWbbMXyR+P1+8VFlg36snScZXIVa+nfL+z5aJs3deoxjQp/SWlEdYuXJrVgbkL9+6f2sYUAAgi0J7C5RvrHbGnpxuYtV1dKd1k2/o42v/Ape0t9mCO/ORCPEEAAAQRaCRAAbUVCBQIIIIAAAggUq8CMOZIPgY9bfDh8MQdAD7Yhu14SfSwYMatlClvC6sL5QHv0aQjaRe2DB/xAAAEEsgj4e/Gts6RVFuxsqyzZIN32gvSxAySyaNtSoh4BBBBAwAVa/qWKCgIIIIAAAgggULQCi9fm1nUfCl/M5d1H2QJIO0orbXhqtrJsSUJDbPGXU07I1op9CCCAQErgubezBz+jlisqbJE1y8inIIAAAgggkE2ADNBsOuxDAAEEEEAAgaIS6JXjMMpeRb6IVJl53fAD6YMXJFT/cOOvStqcfPMb69YvSOjG70kDGAJfVP890VkE3onAi2lzfrZ3nNlLpIPHt9eK/QgggAACxSxABmgxv/r0HQEEEEAAAQSaCUy1bMZcytSdcmldmG2PPlT66/VS1XxpuQ1FTYt/Bo8r3pB+8W3p5OMLs//0CgEEOl7A5/7cVB3/uBuqpOra+O1piQACCCBQfAIEQIvvNafHCCCAAAIIINCGwMETbUj30DZ2tqj2FZw/dGCLyiJ9+N53Sa88Jn336zYfaJrBt74svWz1H/5AWiWbCCCAQDsCW23+z1zLtjwn13PQHgEEEECg+wrYn+4UBBBAAAEEEEAAARfo2UP63uk2SXp6FK8NmgunSzuPaGNnEVYPGih9/nyzM8OoXPpZacSw6BH3CCCAQDyBfuX2ZUqM9+HoaD2sbd8cpzCJnss9AggggEBxCBAALY7XmV4igAACCCCAQEyBI3eTfnKmNG0Xaa/xzZ+080hp7wnS+cdKX3lf8308QgABBBDoGIFS+yJl/JD4xxpvmfuelU9BAAEEEECgLQEWQWpLhnoEEEAAAQQQKFqBQ3eV3lwfdv+ptEHde09MaNAA6RCb+zOX7KSihaTjCCCAwDYKHLqztGBt+0/2RNHDrC0FAQQQQACBbAJ8T5ZNh30IIIAAAgggUHQCtbaQxpe+kb3b1/9aWrIsexv2IoAAAghsu8COg6R32ZdR7ZXplrU/2qbgoCCAAAIIIJBNgABoNh32IYAAAggggEDRCXz7h9JrbyQ1eYeG4Ja+rvmE4WHdkIEN+thnbE/6kudFJ0WHEUAAge0rcMA46dS9pUG9W59nsNV9cB9pP8vIpyCAAAIIINCeAAHQ9oTYjwACCCCAAAJFI7Dahlv+4ndSbY2tBj8iGdzSh7qPGRrWbd0sPT9buvfBoqGhowgggECXCEyyxebOP0zaf2zq9AdZYPQ8q9tleKqOLQQQQAABBLIJMAdoNh32IYAAAgUqUFWd6tiWqtQ2W4Uv8PpbUvpr/sws6eA9pDJWzw1e/P/8V9pqQ+B9GPySxeHvQ3qW54oVUoMFRysrw333PiSd9N7C/72hhwhkE3jkTZszd6X9d1OfarVgtfSr/0k9bTGbcw9N1bOFwLYI+BdRA3ulnjnQsj/Tv5xK7WELAQQQQACBzAIEQDO7UIsAAggUpMCCRdI3r5Xuui/VvZ/fJL30mvTtr0gH7JuqZ6uwBDZWSBd/XbrjXlsp1+ZVi8pV10m/s9+Bn39fOvbIqLZ47xc2Bj1XrErooq9b5MZKegD0qh/2UMKGvVdaINTL243tw0f8RKA4BbZslTYGX6z5cjRhqWtIBHU9GW8WkXCPAAIIIIAAAl0owJ8kXYjPqRFAAIHOFHjyOVsl9X3Snf+S6huan/mxp6TpH5T+envzeh4VhsAmy1Z8z4fC4GemHi22xXxOOUu6+/5Me4urrndjhlFZf2nyieEtbRF47XxsWDdoQujSKy0jqbik6C0CKYESi3uGt6Rl5YW3Erv3uh582khBsYUAAggggAACXSZABmiX0XNiBBBAoPMEVq2RzjhPqtjU9jnrbejihV+14M5Em2fLFhWgFI7A5ddIr76RvT8NFhQ//xLpkAOk4UOzty3kvXvvmVvv9p2aW3taI1CIAifsIfltk2WCzt0YfsM2rFdCO/VPZYQWYr/pEwIIIIAAAgh0HwG+k+0+rxVXigACCGyzwI9/Ja3b0P7TPQjqQ+QphSOwdr30x1vi9adys3TTX+O1LdRWRxwkTRhrcxlukRY9Ed6S9t9FVJZaJrXXVy63zDYbIf/RU6M93COAAAIIIIAAAggggEC+CpABmq+vDNeFAAIIdKDAP/4d/2CPPS150Gzo4PjPoWX+Cjxur6cHtuOWGY9Ll10ct3Xhtetpfxld/12bEuCT0mKbGsJLSb/w3n8uswCoGqeQ+PLnpEk7p/YV89aSddLtz4YC6XOmXt84rcIJe0u7ji5mIfqOAAIIIIAAAggg0JUCBEC7Up9zI4AAAp0gsNWGJC6xOR7jFg9eLFxEADSuV763W7k6tyvMtX1uR+8erY89whaG+ol0waVSta34nqlcdK50pU0ZQAkF3rZpNn7Y+EVLg72HRCWq22UEAdDIhHsEEEAAAQQQQACBzhdgCHznm3NGBBBAoFMFfJhuIsdp2Er5eqxTX6PtebIhOWby5tp+e157Vx77gydJL86QPNBZkvbX0geOkx65U/reFbn/d9WV/eHcCCCQPwLLNzdo/sZ6rdrSmE5ul7a+JqxbtClVlz9XzJUggAACCCDQ/QX4iNv9X0N6gEBRCzy/wLIVLfPojddTDAss4+0OG6bqK8+ePC1VX6xbHgCdMkl67U0L2NiK1Ql750/W2a26UaTUAjzltm1ZWw02B2R5mbTLhGLVKrx+H3ZgWp/SAnlNtV7nN8/as1uz9k2NinNjxx3CQOfv77I5PxsJ/u8qadSw4vTI1uvJNrz9Z58IW3zhSZtGo0ryL1Kiuv3GZ3s2+xAoLoHNtUltqpW22L/FUamxqUo22oiNshJ/M6YggAACCCCAQEcLEADtaFGOhwACnSrwN5uj7xab47Bubeq0T70lzf6zffi2wB8B0NDlo6dJV3xP6rOXuYySttqQ+C0zw33l46XeUyz4aQGLiofM7Hipb5+UJ1vdW2D0SOnU90n/sNd2oGUveqm0/2ai0u8Q+7Kgrw31tgB5wzzpvI9He7hHIL7AsP42b+r+Yfuv2ZcoXnpY5nlUF9bwEwEEEEAAAQQQQACBrhHIlAvSNVfCWRFAAAEEtpvApz8p7b5r+4cfNNBWgf9y++1o0b0ErvuW5IHQ9sq1V0pjd2yvFfsRQAABBN6JwNj+JZoyuESDffRFY+ljaSleN3EQH88iE+4RQAABBBDoSAH+he1ITY6FAAKdLnC8ZTRePN0+NAxNnbq3fYj41KHSlyyTkRIK9Lah73f8XhpiWbFbl9uq4NF4XtudtCF3Xtdjo3SntSEAVni/NSOHS//8g01vYK91nb3OPgVCVOo32WO7nW7/vZx3ZlTLPQIIIIDA9hIos/ToXj0Tsv83lRLb9rpyT52mIIAAAggggECHCxAA7XBSDogAAp0psNqGu//8m9LzM1Jnrdwg/ehr0pz/2DBvG9ZNCQV2GiO9YAHOy99tQ6FrUyqltn3+frbvV9KBdk8pTIHdd5Hm2Wv8l3OkMb1TfbzYhsDP/j/phs+n6thCAAEEEEAAAQQQQAABBApJgABoIb2a9AWBIhP45R8sY+2L0rr1rTueTEp/utXms7RFObZa1hslFOhlmaCfP1/66Kkpkf2mSldbwHjYkFQdW4UrMP0oy5hOmw7Bfxd47Qv39aZnCCCAAAIIIIAAAgggEK77igMCCCDQ7QTemCtd9p32L/tJWw3+uhvab0cLBBBAAAEEEEAAAQQQQAABBBAoTAFWgS/M15VedWOB/7wiPfa6ZTWuSnXi9WXSlbeHj7/2fluxuyy1r1i3fn6TzWNZH6/33vYrn7PVz0vjtacVAggggAACCCCAQH4IbK1Pygb2qM5/KJwjtbYhqRr7O9Af+ZyqFAQQQAABBNoTIADanhD7EehkgZkLpN891nyRmkVrwzq/lEtOIADqDo8+4T/jlU224M+sl6SDpsVrTysEEEAAAQQQQACB/BCYX9GgKlu8b8UWD3SGwc4VW5IqXZdUH/s0O3mwrfBIQQABBBBAoB0B5gBtB4jdCCCQnwKr1uR2Xbm2z+3otEYAAQQQQAABBBBAAAEEEEAAgXwVIAM0X18ZrqtoBU4/WDpkomUsvip945GQYVAf6Y+fCbf7lhctTbOODxksbd7SrCrrg6Es8JPVh50IIIAAAggggEA+CvQrTai0JKmeaSPde1oazwCbEqqc4e/5+JJxTQgggEBeChAAzcuXhYsqZoEJwyW/1W1KKZTZf6lHTUk9Zks6/CDp73fGk+jTW/KVzikIIIAAAggggAAC3Utgx37hoMVFqxuaLryfzeu+y0CGvjeBsIEAAggg0K4AAdB2iWiAAAL5KPC5c+IHQM/9uNSrVz72gmtCAIF8FdhoGeZ3vxBeXV3qM7duf04aOEA6cGebd250vl4914UAAggggAACCCCAAALpAuHXaek1bCOAAALdQGDvPaWvf6H9C93TMmcv/2L77WiBAAIIpAus3Ch97ZbwVmuLb0Tle/eEdU++FdVwjwACCCCAAAIIIIAAAvkuQAA0318hrg8BBNoU8ADo97/RdnbnCdOl+26W+tocqhQEEEAAAQQQQAABBBBAAAEEEChOAQKgxfm60+tuIDB/Yeoiq2uk9ZaNRGkt8LlPSa8+Jp18fGrfkEHSjH9It94oDR6YqmcLAQQQiCsw3Ia5f/OU8LbD4NSzLjsxrDtwl1QdWwgggAACCCCAAAIIIJDfAswBmt+vD1dXhAIvviJd9DXpxbmpzm+ssIne95cuPMc+eF8qldrE75SUwMgR0hGHSHfeGtYNGyodsG9qP1sIIIBArgKD+0rnHRM+608/khY3HuCrRdozAABAAElEQVSsI6X+/XI9Gu0RQACBlMB/bQqNZfbF9qaa1LLm81Yl9PdKqV+5dBILN6aw2EIAAQQQQKCDBAiAdhAkh0GgIwQee0o65SypxjI+E7ZyeXrZWitd/2tptgVI7/wDQdB0G7YRQAABBBBAAIHuIrByk7RovV9tKgBaacHQSvv7bwCLNnaXl5HrRAABBBDoZgIMge9mLxiXW7gCnuV55oVh8DNbL2c8IX3vJ9lasA8BBBBAAAEEEEAAAQQQQAABBBBAIBIgAzSS4B6BLha46a/S2iAboP0L+ZnNbXmJBUtZ3Kd9K1oggAACCCCAAAL5JOBD3OvqpY01DVq8ORlc2ojeCY3oXaIS0lPy6aXiWhBAAAEECkiAf2IL6MWkK91b4MFH419/VbX0xDPx29MSAQQQQAABBBBAID8Eettc7v1tqHtfm++zl237rU9ZY53dUxBAAAEEEECg4wXIAO14U46IwDYJLF2e29OWrsitPa0RQAABBBDYXgJr1klPzwyPXlUV3tdbhtu9D4bb0/aWRo/cXmfnuAgggAACCCCAAAIIZBcgAJrdh70IdJpA//65nYpViHPzojUCCCCAwPYTePV16Yzzmx+/ti5V98efS6ed2Hw/jxBAAAEEEEAAAQQQ6CwBhsB3ljTnQaAdgYP3a6dBi90H7tuigocIIIAAAggggAACCCCAAAIIIIAAAq0EyABtRUIFAl0jcPZHpd/+RUqGc+FnvYj3HCON3TFrE3YigAACCCDQaQL+b9IXL2j7dJMntr2PPQgggAACCCCAAAIIbG8BAqDbW5jjIxBTYOoU6dLPStfZMMFsZfAg6UdXZWvBPgQQQAABBDpXYMJY6TuXde45ORsCCCCAAAIIIIAAAnEFGAIfV4p2CHSCwJWXSJddLJW08V/mzuOk+26Wxu/UCRfDKQpSoLJa+r9/Szc/lereC29LX79VWr4hVccWAggggAACuQok04axNKRt53oc2iOAAAIIIIAAAh0t0EaYpaNPw/EQQCCOQCIhXfEl6TlbNffkE1LPKC+TfnGtNPMhac/dUvVshQJrNknPzE1prKuUXlqUesxWKLBgtfTeH0g/vl+qsEBoVGptpeY/PS4d+z3pybeiWu4RQAABBBCIJ1DbkNSiTQ2aX5Gax2ddjfTmhnpVbk3VxTsarRBoLvC8/U33qP19snid/aHcWN5emwjqZi2OarhHAAEEEEAguwAB0Ow+7EWgSwR8rrSzTk+detBA6RP2uMwCoZTmAr9/TDr029K9L6bq12+WTvihdN6NFuirStUX89YW+yB65i+lt9e0reBWZ/9G8kApBQEEEEAAgTgCVXVJvb6uQWurk2oZ6txcK721sUGrqxriHIo2CGQUeGmZfdG90EaqbEwFQJdtSAR1r9g+CgIIIIAAAnEECIDGUaINAgjkpcBPH5C+cbu0ZWvmy7vvJenDP5Oq2tif+VmFWXvjo9LCLMHPqNebLVB67T3RI+4RQAABBBBoW6DehrnPswCnxUCzliWVSW0iEzSrETsRQAABBBBAYPsKsAjS9vXl6AggsJ0EXl1qC0b9q/2Dv7IknPPyipPbb1vILe6cGb93D7wseSC0b3n859ASAQQQQKD4BFZXJVUbM7lz6eYG7VbWo/iQ6PE7Fjh2V6m6TtpY06B1lmnsZWjvhAaUlah36Ts+PAdAAAEEECgSATJAi+SFppsIFJrAjTPUaqhdW330+S2rbRhesZY6m+Nz3qr4vfc5QRfk0D7+kWmJAAIIIFBIAhtq2kn9TOtslQWwaurjt097KptFLjB2iLTrCGncUGnEoPDm21630+Aix6H7CCCAAAKxBQiAxqaiIQII5JPAU2mLHrV3XT5E/uUiniTf1qZQrovx8hm1vd8q9iOAAAII1FhQM5dSY1+wURBAAAEEEEAAga4QIADaFeqcE4EsAh6ounuWdM3dqUZrbVXzr98qLV2Xqiv2LV/pPZfihsVaymyyk50seyJuKbE1BsYNi9uadggggAACxSqQSK1JE4sgx+axjkkjBBBAAAEEEEAgjgAB0DhKtEGgkwR8pe4P/8rmrJwhrU/PqrBPDE9YBuPH/yD98/lOupg8P82w/uEFDugnjRwu9e+buuAeFvDzupFpQbxh1q6Yy0n7xe/9kbtJg/rEb09LBBBAAIHiFOhl/97mUnJtn8uxaYsAAggggAACCGQTIACaTYd9CHSywBf/Gs7V2MsWnylLm9TdMyyCujLpS9Zm5vxOvrA8PN1hNiG+l34W+Bxm8z/1TQvY9bR3Nq8b0jgvVD/z3Gts2L5Yf37mWDNpDBpnMyi19Sm+dlK2FuxDAAEEEEAgFBhSHj+ns7/9XVPqQwwoCCCAAAIIIIBAFwgQAO0CdE6JQCaBx16X/vVipj3N6+pstdXLb29eV4yPzjtaivs56pyjLKCcY5ZKoZkOtkDxHz9tQeG0TNmWffTg588+Ie2xY8s9PEYAAQQQQKC1wNBeCfWJ8e+rhz3H9ONjR2tBahBAAAEEEECgswT4S6SzpDkPAu0I3PZs2GDVWunVN22+zxWpJ/i8oF7ntwYLgL66RJqzLLW/GLd2HS1942Rp7Xrp7aVSRdocn/Vm5HWL7TZtgvT59xajUOs+7z1WeuCr0hkHS54lGxX/YDp9TwvAXyqduG9Uyz0CCCCAAALZBRI2RGXngSXqnSUI6l9Whm38XxsKAggggAACCCDQNQJpH4G75gI4KwIIhAKvWbAul5Jr+1yO3V3anneM9L0PWSaoBTxra1NXbfFiVW6WjrOg3t8vlMpLU/uKfWv0IOmHH5U+eWRKYr8J0h/Ol3Yfk6pjC4FiF5i3UJpyWHh7xTL0o3LAu8O6v90R1XCPQHEL+LD2XQeVaEzfhMrSPll4uHOYZYhOGVyiAWUEP4v7t4TeI4AAAggg0PUCWb6v7fqL4woQKCaBremLHsXoeK7tYxyyWzb58EEW6NxLuvAntkDUf8Mu+CILMy6XJo7sll3qlIvukfZZNH27U07OSRDoBgJb7UsVzyJvWZYsD2vSs85btuExAsUmUGKZoCP6JCwTNKm5G+1bSSs+PH6n/mkR0WJDob8IIIAAAgggkFcCBEDz6uXgYopZYIKtWr5gdXyB8WkrnMd/VmG2HNBbmjQq1TfP+CT4mfJgCwEEchfwYbtltvBcW6UHcZ22aKhHAAEEEEAAAQQQQCDvBAiA5t1LwgUVq8Dxe0uPvBav98P6SQfsHK8trRBAAAEEcheYPFFaZ/MuUxBAAAEEEEAAAQQQQKD7CxAA7f6vIT0oEIEPHij9dob0ZtriR2117asn2SI2tmI3BYFcBRbakN6Nm6TVa1LPrLQFpGbbHIdlljk7ZZdUPVuFJeDz5M54POzTaltsLSr/e1qaO98WKRlvmdMTolruEUAAAQQQQAABBBBAAIHCESAAWjivJT3p5gKlFtC86Tzp9J9Jyza03ZnzjpY+ckjb+9mDQDaBkz5tUy280rzFC09Ihx0n9eovrXm5+T4eFY6AB75PPbt1fz771bDuK5+Trry09X5qEEAAAQQQQAABBBBAAIHuLsAMVt39FeT6C0rA5wG978vSxw6VPCCaXnYZIf3yLOmbp6bXso0AAggggAACCCCAAAIIIIAAAgggkE2ADNBsOuxDoAsEamzx1DMOlwba1xPX3B9egA93v/6scLve9rP4Rhe8MAVyysm7SXX10uZqqWJL2Kne5dKgvtKAgQXSSbqRUaB3L+lzn8q4K6g8ZP+297EHAQQQQAABBBBAAAEEEOjOAgRAu/Orx7UXpMBbq6SnF0pv2H1UkknpwTnhoykjCYBGLtznLnD7D8PnXHef9BO7eTl6D+kvNjSeUtgCfftI3/9GYfeR3iGAAAIIIIAAAggggAACmQQYAp9JhToEulCgwaOdWUqynf1ZnsouBBBAAAEEEEAAAQQQQAABBBBAoOgEyAAtupecDue7wOD+SU3eIalVy/xKw+8oEgrrvCZRkvA7CgIIIIAAAggggAACCCCAAAIIIIBADAECoDGQaIJAZwqMsJW4kz2TetnmZEwv40aEmaE9CYCms7CNAAIIIIAAAggggAACCCCAAAIIZBUgAJqVh50IdL5AL/uvcmCZ5Xw2NB8K38sCn71KLSeUBNDOf1E4IwIIIIAAAggggAACCCCAAAIIdFsB5gDtti8dF16oAm+vLtFVd5Xoybmp/zw9FPrFv5fojmdLVFNLBLTla7+iwhaNWpGqramTZi1OPWYLAQQQQAABBBBAAAEEEEAAAQSKV4AM0OJ97el5Hgo8OV/6jq3M7cmfLcOcHgR96HVp4Trph6coyAbNwy506iX5elC/f1p6fJ709vrUqesbpJ8+Ku00SPrSsdJgW/2aggACCCCAAAIIIIAAAggggAACxSmQSjErzv7TawTyRmBDlfSDh8LgZ7aLemtVGPTL1qZY9t34pDR7qTR5pDQkLcjZw6LHU0ZJfcqlS++UNtcUiwj9RAABBBBAAAEEEEAAAQQQQACBlgIEQFuK8BiBLhK452Wpqjbeye+1tsUe1Hvdhrzf/kL7Xks2SH+wLFEKAggggAACCCCAAAIIIIAAAggUpwAB0OJ83el1HgrMWhT/oupsiPfLy+K3L8SW/3wp7NUqm//Ts2Ir07I8jSeom7s6bHP/a1J1zOByIVrRJwQQQAABBBBAAAEEEEAAAQSKWYA5QIv51afveSWwfktul7Nuc27tC631K40B4JdmSOtsDtC6tABopQWT/3WDzaPaQ5p6urS1PgyITh1TaAr0BwEEEEAAAQQQQAABBBBAAAEE2hMgANqeEPsR6CSBfr3sRJbNGLf09/ZFXDY1BjyrbPGjTS2yYeurw7pEWo571L6Iyeg6AggggAACCCCAAAIIIIAAAkUpkBYeKMr+02kE8kZgz9G5XcruObbP7ej53zp90aM4V5tr+zjHpA0CCCCAAAIIIIAAAggggAACCOS/ABmg+f8acYVFInDSVOlum9eyPtl+h4+cKA3t2367Qm6x307Sso3SzsdK44+SGmyOzzcb51EdPsh8hqZ6389Wg580IvW4mLeS9vv137nSEzZtQFQWrJXust+94/eQymzaAAoCCCCAAAIIIIAAAggggAAChSRABmghvZr0pVsLjLGg3acObb8LHvj8zBHttyv0FqftK/Wwd7AepVJp7/BWUib5rYdNDxDVucOHGtsWukl7/auwqQFOtblRL/6zNGdJqvVKm0bgG7dL038gLbFtCgIIIIAAAghsX4GkfSNZbXOUR8XnK/c6CgIIIIAAAghsHwEyQLePK0dFYJsEPKhXahl4v31CyrRo+a6WxXj5cdKQIs/+dNwdBlog72hpwcYG7Tc+qX/NtKDegjB9sXdpUled1qB6Ww7+npk99KH9tunlKKgnucW3/mVGS6XKFgtoVdt8qn6rqJS+epd0gy0cNciCyhQEEEAAAQQQ6HiBiq1JLalsUE1aAHRdTVJeP6ZfQkN6kaPS8eocEQEEEECg2AX417XYfwPof94JvH8v6Q+fkPZIm+MzYVf57fdJP/2QNGpA3l1yl13QcbtL+4+zYdv2VU6PFkO3va7cskOvOjHMFO2yi8yTE9//mvTq8vYvZo0FQf/0TPvtaIEAAggggAACuQusrW7QPPvyNj34GR2lzhJA396U1LLN9q0lBQEEEEAAAQQ6VIAM0A7l5GAIdIyAD3NvOWflwRM65tiFdpTXF0mzFib0RtpK8Os3SX98OBFk006zoDFF8gColxE2N+pQm24hU0l4pN3Kw69LF9g0C8wHGnrwEwEEEEAAgY4QqLII5yILcLZXVm5Jqm/PpAaWN/7D3N4T2I8AAggggAAC7QoQAG2XiAYIIJDPAi/OL9FtTze/wootCd3+ZBgAvY4AqBrss9bc1aFRb5sftb1SXScttblAJwxrryX7EUAAAQQQQCCugAc245blWxosANpieEvcJ9MOAQQQQAABBFoJMAS+FQkVCCCAQGEJ1NkcYx4EzaXUWBCUggACCCCAAAIdJ+BzfMYtVfbvcG2u/3jHPXg3bOfZsxvT/CpszlSvoyCAAAIIIBBXgAzQuFK0Q6CTBN6cJ81/W3rtldQJ66psCPMj4ePpR0o9+S+3Cecc83jPntLzi5O65+VwqNiOg5I699CEShg5Fjj5fKiD+0jrtzSxtbsxkrlm2zWiAQIIIIAAAnEF6i2YWZ9jvK7WvsAsLfJ0lYakLxiV1Nrq5ngVtlpoxfoGDe2V0I62cFRJNI9P3BeEdggggAACRSdAGKXoXnI6nO8Cf7ld+tEv/SpT0buatQl98JzwypfMthW6bQV0Siiwx462YJTd6m2U2H8XhHU72NDt99piUpSUwCETpH+/mnqcbWvyyDBgmq0N+xBAAAEEEEAgvsC2fCm7Lc+Jf0X53zJpwc8FFQ2q2Nr2tXpgtM6CyxMGlChBELRtKPYggAACCKjIv1PkNwCB/BN4am72a6qwbFAKArkKnD5NKo/5ldcnD8r16LRHAAEEEEAAgWwCHpzrE/PfYT9OD/sevNinAPXgZrbgZ+S90QKk62xIPAUBBBBAAIFsAgRAs+mwD4FOFqi24TwabH/w7tL2bd66Tr4oTlcQAqNsSPtl77HpE9p51z/7EGna2ILoMp1AAAEEEEAgrwSG2XDtuMWHdhd7RuPqqvhBzVzaxn0NaIcAAgggUFgCOXwPWVgdpzcI5KPAXS9Jwyz4Ocb+y0za/7ZsDf9Q7lmStOy9cPvxt6VxI6SdWaE7H1/CvL6mQ3eWPn+M9LjNM/u2BdJXVISX6/ODjhsi7WNTCZxhmaIUBBBAAAEEEOh4gSEW1FxvmYqb/AvvLMUzP0f1Cf/uy9KsoHf5sPZqmwM1bvFFo+ptyHwPhsHHJaMdAgggUHQCBECL7iWnw/kq8NYqaaEFpfaxIJXf6hqkx94Kr9az93Yfnbryh9+QJgy1WUKL+2/jFAhbsQUqqqW+5RZo75cKgA7sJQ3pm9siSbFPSEMEEEAAAQQQCAQ8o9Pnqly4qe15LX2YvLfpUeQTgOa6YJQD19vfzj0seExBAAEEEEAgkwAB0Ewq1CHQBQKvroh/0nW2mrdn741mMaT4aLREAAEEEEAAAQS6WMADm7sM7GFzWya1YnODNlvmopco63NwOUPf3aNx4JNvxi7tTfMT+0A0RAABBBAoSIF2ZoMryD7TKQTyUmBNZW6XtWZzbu1pjYALHGbZxR/cR5o0POUx1LJBve59e6bq2EIAAQQQQACB7ScwoCyh4b1TQ3k88DmkFyuZR+IeKM5l0ai+pVIJQ6MiPu4RQAABBDIIEADNgEIVAl0hYNMW5VRybZ/TwWlcsAKeNbyLBT8H2byfUellHxq8zucBpSCAAAIIIIAAAvkgMLJP/I+qI3vHb5sPfeMaEEAAAQQ6X4B/KTrfnDMikFHA52DMpQzNsX0ux+5ubVdvkhavT131Vps0//WVtpBUjkHl1BHYQgABBBBAAAEEEOhKgUGWFTvUFo5qrwyzNgOtLQUBBBBAAIFsAswBmk2HfQh0osCUkdLc1RbIs4WQlm5sHrxbbcPjn14QXsz+42zBGsve24H5P2ULhGrGm9LMRVJN4xxartRgk+Df9ZI0sr90yt7SwN6d+EJyKgQQQAABBBBAAIEOEdipX0JltrDRis1Jtfxe2zN5RvVNKJdM0Q65KA6CAAIIINAtBQiAdsuXjYsuRIEpo8JA3jwLgm7Z6j1MfZNd35BorAsDo8fsygrwLvTQ69J/7FZZE6786XVeNtgiUQvXSm/brapW+uRBUp+ycB8/EUAAAQQQQAABBLqHQMLm9RzVJ6FhvZJaXNmgDfY3n5fB5dKO/UrU0+YKpSCAAAIIIBBHgCHwcZRog0AnCPi87Z6t2NvmY8xWfBGb3SxbtNjLIsuUfXGJ5MPf56+xYOe61B/AG6oSQZ3XV1RL/32r2LXoPwIIIIAAAggg0H0FPNDZN21p+L6lCYKf3ffl5MoRQACBLhEgA7RL2DkpApkF+veSrjvFhrsvlOasTFomYxjUG9AnKV8t9PBdWKgmkptlwc+45ZXl0rsmS+W848Ulox0CCCCAAAIIIIAAAggggAACBSNAOKBgXko6UigCZfZf5ZETpYm2Kvefnw171deyQj92QKH0sGP6sXRDeJzRg8IVzctLk6qpDQPGfcqT2lKTaJpEwOcKXVkhjWWV847B5ygIIIAAAggggAACCCCAAAIIdCMBAqDd6MXiUotLwIfEN5X07abK4t6IFj0aZAsc+a2fZc9W2nB3L4P62jygm8Pt6GfUPnrMPQIIIIAAAggggAACCCCAAAIIFIcAc4AWx+tMLxEoOIH+Nvl9LqVfju1zOTZtEUAAAQQQQAABBBBAAAEEEEAgfwUIgObva8OVIYBAFoGdh2XZ2WKXrwA/akCLSh4igAACCCCAAAIIIIAAAggggEBRCBAALYqXmU4iUHgCB4yTrf4Zr1+HjJeaTSkQ72kF2erlZdKjb0rz16S6t3pTWPfU/FQdWwgggAACCCCAAAIIIIAAAggUigBzgBbKK0k/Ckqg3lbtqdjaYH3qEfTLF/HZXJtU31ImA41e6AE25+f79pTufkkynjbLriOkaWPb3F10O26bJT2zsHm331wlfe9BaZjNnXrIzs338QgBBBBAAAEEEEAAAQQQQACB7i5AALS7v4Jcf8EJrK9u0OJKC4BWpbrmAdA3NzRogA3lHtu/RKUlBEJdZ7eRUu9p0oNzpCBenCILskMPGi8dagE9sj/TYNhEAAEEEEAAAQQQQAABBBBAoMgECIAW2QtOd/NbYK0FPxdtajufsWKr9JYFQncdVGIBPoKg/mqOGyJ96lDpuUXhMG6v8wWPPnmA1KvUH1HSBY7ZVZo0XFqzWXp9Zbhnp0GhY18WikqnYhsBBBBAAAEEEEAAAQQQQKBABAiAFsgLSTe6v8DW+qQWZwl+Rj2sqZeWbk5qXH8CoJGJx4IH944eSeX2zkbwM+WRvuUBUC8e/Nxqv0teDpkgHTkx3OYnAggggAACCCCAAAIIIIAAAoUmQAC00F5R+tNtBdZUJbPOZZnesXXVSY3pmyQLNB2F7VgC8zfWa6NlEq+o8ObhHLMrtzTohdVJm1pB2nNoWBfrYDRCAAEEEEAAAQQQQAABBBBAoBsI2MddCgII5IPAJlvkKJdSWZtLa9oiEArk9luGGgIIIIAAAggggAACCCCAAALdX4AAaPd/DelBgQjU+aLvOZQ6XxmJgkCOAr6AVpm986fnefpkCl5Xll6Z43FpjgACCCCAAAIIIIAAAggggEC+ChAAzddXhusqOoGeOf7XyCJIRfcr0iEdHtu/RMMt0rmlOvULV1ObUF8Lie46iAhohyBzEAQQQAABBBBAAAEEEEAAgbwSYA7QvHo5uJhiFuhfmtCWuvhZnf1Y4byYf122qe/1lmX88BvSC0ukgX1Sh9hcI90yS5owVDppqtSb360UDlsIIIAAAggggAACCCCAAALdXiCVAtTtu0IHEOjeAsN6JxR3XfchvRIsgNS9X+4uufp/vRIGP9s6+YK1Fgh9XqptXB2+rXbUI4AAAggggAACCCCAAAIIINCdBAiAdqdXi2staIGyHgnt1L/9EGi5jVIe07f9dgWNRedyFnhjpTTHbu2VlZukpxe214r9CCCAAAIIIIAAAggggAACCHQfAQKg3ee14kqLQGBorxKNH1Aii4VmLAPKZPM0lpD9mVGHymwCsxZn29t83wvWNhl/NobmT+YRAggggAACCCCAAAIIIIAAAnkmwBygefaCcDkIDC5PaEBpieauSy0Lbwt3B4HPvjZPKAWBbRFYuiH+s6pqpbWbpWH94j+HlggggAACCCCAAAIIIIAAAgjkqwAZoPn6ynBdRS3QwyKeA8pS/3l6AJTgZ1H/SryjzvucnvU5ZnTW1L2jU/JkBBBAAAEEEEAAAQQQQAABBPJGgAzQvHkpuBAEQoFVNgfjmkppfVVKpGqr9Nry8PHkkVKPVGw01aiItyprk1pX4xmzNkGqla0W7VtTlZQvFlWSIGu21FjK7d0+l6Bmv/KAkh8IIIAAAggggAACCCCAAAIIdHsBAqDd/iWkA4UmMGdFtAhNKnC3YUtC99gK3l52HkYANJSQGmyiysWbPPiZ1Ja0jEUPhS6uTGrVlqR2HliiXj1TltFzi+1+wlDp9RiLILnLkD7SwN7FJkR/EUAAAQS2VWCLfRG51f7xrapLDTeosS8jN9i/z/4v8ECb3oeCAAIIIIAAAgh0pQB5ZF2pz7kRQOAdCSxqDH62dRBPCn1rQ4Nqcx3/3dYBu3H9wePjX/whE+K3pSUCCCCAAAKrbdTFgooGrbAvHqOyyeaT9jq/URBAAAEEEEAAga4WIAO0q18Bzo9AC4HxlqnX04Ys1zUk5R8ovJTb4yG2QrwX30eRKrYmtd4yS9ornoyydHNS4wcUd/bJyAHSu3aVHnkzu9jUHaQ97UZBAAEEEEAAAQQQQAABBBBAoFAECIAWyitJPwpGYNwQyW/VNqR7zvowwDegTNplYMF0sUM6sqYqfkaJB0p3tIByT19NqojLAeMkn9vz4TdaI/g8oYda5udB41vvowYBBBBAAIFsAv53Slv/xjIVdzY59iGAAAIIIIBAZwkQAO0sac6DAAIdKrA5bc7POAeusvb97QNasZcpo6RJw6X/zpdmLgw1hvSVPnGA1Ku02HXoPwIIIIDAtggMtlEqg7fliTwHAQQQQAABBBDoJAHmAO0kaE6DAAIdK2AJnTmVXNvndPBu1tinURiUtshRHwsME/zsZi8il4sAAggggAACCCCAAAIIIBBbgABobCoaIoBAPgmU5fju5UO8KQgggAACCCCAAAIIIIAAAgggUHwCDIEvvtecHiNQEAIDyhKq9lVnVya0uiKhuvpUt1ZvTOjZ6oR83rEDJjao1IKlvQmApoDYQgABBBBAAAEEEEAAAQQQQKCIBAiAFtGLTVcRKCSBEX0SWlOd1OYaacPm5osbba1LaKvN+fn/7d0JmBTVucbxb9j3EQRRQFAWF8CNKFyXEEQMLol6I5gQjXgjARTBLRoXVMw1CDEmasAtKo8aFKNGrxHRuIEYggsSEQQ0IILsiwjIDnP7Pabanp7qnupleqq7/+d5humuOnXqnF91F93fnKWk5Jtx8vtH8pawCkMhXX7aggACCCCAAAIIIIAAAggggEBggRQHkQYul4wIIIBAlQrUjqzoflDjGlY+9FnxlM3qlVjz+tzqKsqwBQEEEEAAAQQQQAABBBBAAIHiEKAHaHFcZ1qJQEEKlNYtsTM7my3bvMe2xQyBV2NrRiKj+9UvsbaRICkJAQQQQAABBBBAAAEEEEAAAQSKV4AAaPFee1qOQEEINI0EOZtGJvhcv22vLd3yzZD3xrXN2pfWsBoMey+Ia0wjEEAAAQQQQAABBBBAAAEEEMhEgK5RmehxLAIIhEagrrp8/ifViTwm+Olp8BsBBBBAAAEEEEAAAQQQQACB4hYgAFrc15/WI4AAAggggAACCCCAAAIIIIAAAgggUNACBEAL+vLSOAQQQAABBBBAAAEEEEAAAQQQQAABBIpbgABocV9/Wo8AAggggAACCCCAAAIIIIAAAggggEBBCxAALejLS+MQQAABBBBAAAEEEEAAAQQQQAABBBAobgECoMV9/Wk9AggggAACCCCAAAIIIIAAAggggAACBS1AALSgLy+NQwABBBBAAAEEEEAAAQQQQAABBBBAoLgFCIAW9/Wn9QgggAACCCCAAAIIIIAAAggggAACCBS0AAHQgr68NA4BBBBAAAEEEEAAAQQQQAABBBBAAIHiFiAAWtzXn9YjgAACCCCAAAIIIIAAAggggAACCCBQ0AIEQAv68tI4BBBAAAEEEEAAAQQQQAABBBBAAAEEilugVnE3n9YjgAACxSXw0QqzdVvMVm/+tt0rN5q9+YlZvcj/CMe3/3Y7jxBAAAEEEEAAAQQQQAABBBAoBAECoIVwFWkDAgggEFBg4WqzReuUuSR6xLotJS4o2rguAdAoCg8QQAABBBBAAAEEEEAAAQQKRoAh8AVzKWkIAggggAACCCCAAAIIIIAAAggggAACCMQL0AM0XoTnCCCAQAELdG6910qblNnesoqNbFavxMrKSqyk5NveoRVzsQUBBBBAAAEEEEAAAQQQQACB/BIgAJpf14vaIoAAAmkLrPh6r+0oKbPmTRIVUWaLN5VZ+yY1CIImImI7AggggAACCCCAAAIIIIBA3gkwBD7vLhkVRgABBFIX2LKrzFZv9en2GVfUpp2RRZK2V54v7jCeIoAAAggggAACCCCAAAIIIBBaAQKgob00VAwBBBDInsCarXsDF7YmQKA0cGFkRAABBBBAAAEEEEAAAQQQQKCaBQiAVvMF4PQIIIBALgQ2R3p2Bk07I7HSHXvoBRrUi3wIIIAAAggggAACCCCAAALhFmAO0HBfH2qHAAIIZCywtyyy6FGKpeyOHFC3ZooHkR0BBBBAAAEEKhXQnNxbI1PT7Ir5z3lDZPqZr3ftsdo1SqxdZC5uEgIIIIAAAghkV4AAaHY9KQ2BjAU2bN9rX+0os9gOeFt3mX321R5Xtj4U12CV7oydi6kAvV60rnsqfTprshB8Mb1EaCsCCCCAQA4FFPzcHPlsF5s0+kI/dWqk8r91bAmF+3hx5DPw9sjH4D0xAeNVX5fZ2m17rH6tEjuYgHHhXnxahgACCGRRgABoFjEpCoFsCGzfbbYxbrjy7shnYW/bgZHHkc4BJARSEmhU2yp82UpUQK1IxxN6fybSYTsCCCCAAAII5FLgm6l5yp9Rn413R4KiNUsIGJeX4RkCCCCAQCIBAqCJZNiOAAIIFJDAfg1q2OavYrpOJGnbfvUjPUbpZZxEiF0IIIAAAgikL6DRPHsTxO34G3f6rhyJAAIIIIBAMgECoMl02IdANQi0aFBiTesl/vjL0ORquCgFcMomdUqseeR1tS4yx1iypJ6iCoCSEEAAAQQQQKBqBDTPJym4wGFNa1pZZD5zv8QfbP1U2IYAAggg4CdAANRPhW0IVKOAPhTXZu77arwChXvqNo1KTMPbV28t850PtFndEjuwMb0/C/cVQMsQQAABBBDITwECnfl53ag1AgggECYBAqBhuhrUBQEEEKhCAX15OKBhie1br8y0Au2XO745WcPI/wQHNq7hFhKowtNTNAIIIIAAAggggAACCCCAAALVIkA/s2ph56QIIIBA9QnUicyjUFr329t/o8jweK2iSkIAAQQQQAABBBBAAAEEEECgEAW+/QZciK2jTQgggAACCCCAAAIIIIAAAggggAACCCBQ1AIEQIv68tN4BBBAAAEEEEAAAQQQQAABBBBAAAEECluAAGhhX19ahwACCCCAAAIIIIAAAggggAACCCCAQFELEAAt6stP4xFAAAEEEEAAAQQQQAABBBBAAAEEEChsAQKghX19aR0CCCCAAAIIIIAAAggggAACCCCAAAJFLUAAtKgvP41HAAEEEEAAAQQQQAABBBBAAAEEEECgsAUIgBb29aV1CCCAAAIIIIAAAggggAACCCCAAAIIFLVAraJuPY1HAIG8F9i6q8x27jXbtrss2pYde8ps445vnu9TtyS6nQcIIIAAAggggAACCCCAAAIIIFB8AgRAi++a02IECkpg7fYy2xD5iU1bdplt2bXXFPo8ukXN2F08RgABBBBAAAEEEEAAAQQQQACBIhNgCHyRXXCaiwACCCCAAAIIIIAAAggggAACCCCAQDEJ0AO0mK42bUWgAAVK65RY7QR/ymHwewFecJqEAAIIIIAAAggggAACCCCAQIoCBEBTBCM7AgiES0BzfDLPZ7iuCbVBAAEEEEAAAQQQQAABBBBAIEwCCfpNhamK1AUBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEhPgABoem4chQACCCCAAAIIIIAAAggggAACCCCAAAJ5IEAANA8uElVEAAEEEEAAAQQQQAABBBBAAAEEEEAAgfQECICm58ZRCCCAAAIIIIAAAggggAACCCCAAAIIIJAHAgRA8+AiUUUEEEAAAQQQQAABBBBAAAEEEEAAAQQQSE+AAGh6bhyFAAIIIIAAAggggAACCCCAAAIIIIAAAnkgQAA0Dy4SVUQAAQQQQAABBBBAAAEEEEAAAQQQQACB9AQIgKbnxlEIIIAAAggggAACCCCAAAIIIIAAAgggkAcCBEDz4CJRRQQQQAABBBBAAAEEEEAAAQQQQAABBBBIT4AAaHpuHIUAAggggAACCCCAAAIIIIAAAggggAACeSBAADQPLhJVRAABBBBAAAEEEEAAAQQQQAABBBBAAIH0BAiApufGUQgggAACCCCAAAIIIIAAAggggAACCCCQBwIEQPPgIlFFBBBAAAEEEEAAAQQQQAABBBBAAAEEEEhPgABoem4chQACCCCAAAIIIIAAAggggAACCCCAAAJ5IEAANA8uElVEAAEEEEAAAQQQQAABBBBAAAEEEEAAgfQECICm58ZRCCCAAAIIIIAAAggggAACCCCAAAIIIJAHAgRAs3iR7r77bhs0aJDdcssttnfv3qQlP/rooy7vX//616T5gu7cs2ePrVixImj2jPItW7Yso+MrO/iFF15wNpMmTYpm9dsW3ckDBBBAAAEEEEAAAQQQQAABBBBAAAEEEggQAE0Ak85mBQYXLlxob7zxhj377LNJi1i1apXLu27duqT5guxcsGCBXXzxxfb6668HyZ52HgVZ77//fneutAsJcKBM5Lh69epobr9t0Z08QAABBBBAAAEEEEAAAQQQQAABBBBAIIEAAdAEMJlufuCBB+yLL77ItJhAx0+ZMsUWLVoUKG8mmbZs2WITJ060Xbt2ZVIMxyKAAAIIIIAAAggggAACCCCAAAIIIJAzAQKgVUBdo0YN27Fjh40ePbrSofBVcHqKRAABBBBAAAEEEEAAAQQQQAABBBBAAIH/CNRCIvsCP/rRj0xzVn700Uf29NNP249//OOUT7J7927Xq/Ozzz6zmjVrWseOHe3AAw+0WrW+vWQakr506VLbtGmTK3/Dhg2m/KWlpdasWbPA59Tw8s8//9yWL19uTZo0sTZt2li7du2sdu3a0TKUx5tjtKyszJ1HO5VPAd8gKch5gpRDHgQQSF/giy177etdZbY7Zpri9dvLbPPOPVYr8lbuUFoz/cI5EgEEEEAAAQQQQAABBBBAAIEQCnwbTQth5fK1SgpUDh482MaNG2cPPvigHX/88da2bdvAzZk5c6bdc889Fr/YkMq48cYbrXPnzq4sBT4vvPDCaLnPPPOM6UcB18suuyy6PdGDNWvW2NixY+3dd9+tkKVVq1Z2/fXX29FHH+32adGm559/3j1W4NU77yuvvGINGjSocHzshlTOE3scjxFAIPsCO/aU2dbd5ctVMFQ/tYP9LaP8wTxDAAEEEEAAAQQQQAABBBBAIOQCBECr6AL179/fpk2b5nqB3n777TZ+/PhAPSVnz55t11xzjatV79697YQTTjD1uHzrrbds+vTpdskll9idd95pxx57rAs8jhgxwqZOnWpz5sxxgdbjjjvODjnkkEpbtXnzZrvoootMvxXk7N69u7Vu3do++OADmzFjhuvtOXLkSLeYU926de3kk0+2Fi1a2J/+9CfXDi/AWqdOnaTnSvU8SQtjJwIIIIAAAggggAACCCCAAAIIIIAAAikKEABNESxodg0LVw9KBRnnzp1rf/nLX+wnP/lJ0sO3bt3q5g1VpmHDhpXLf9ppp9kjjzxiEyZMcAFQ9chUYFKBVi22pADoEUcc4Z4nPcl/dk6ePNkFP9u3b2933XWXG2avXQq6aij9OeecY1999ZW988471rNnT+vWrZt16NAhGgDVeYOkVM8TpEzyIIBA+gIHN6kR+aNK+sdzJAIIIIAAAggggAACCCCAAAL5JsCAxyq8YhoKP2TIEHcG9ZzUfJ3JkoKNq1atcsPl/QKMGnZ+wAEHuIDnP/7xj2RFVbpPc4r+4he/sGuvvTYa/PQO0vyhXbt2dU/VgzOTlKvzZFJHjkWgmARqlJRYzRqJf4rJgrYigAACCCCAAAIIIIAAAggUhwA9QKv4Ovfr188NUdeCSFoV/t577004FH7JkiWuNhreroWP4pMWQDrmmGNs5cqVbtGi+P2pPNc59OMlzeupchWknTdvXnTBI23PJOXqPJnUkWMRQAABBBBAAAEEEEAAAQQQQAABBApXgABoFV9bDYW/4YYb3FB4BRafeuopGzBggO9ZtRK7knp5JkpanEhJw94zTeptqqH5s2bNcoFPrTzvJb8ArLcv1d+5Ok+q9SI/AggggAACCCCAAAIIIIAAAggggEDhCxAAzcE1btOmjRsKr5XdH3roIbewkd9p1cNTKTYQGZ9vx44dblOmAcqFCxfa8OHDbdu2babzHnrooXbYYYe5eT413+cf//hHy3SYvSqaq/PEO/EcAQQQQAABBBBAAAEEEEAAAQQQQAABCRAAzdHrwBsKr8WKNBS+Xbt2Fc6sQKmShqInSupNqdS0adNEWQJtVx0U/OzTp49dd911bkGl2AO9Ouzduzd2c8qPc3WelCvGAQgggAACCCCAAAIIIIAAAggggAACRSHAIkg5uswlkYVHtCq8Vm7/+OOP3byg8afWiuxK6nnp9fSMzbNlyxabOXOm23T00UdHd2mYvVLQYOWmTZts8eLF7piLL764QvBTgdFly5a5/bFzgHrnKQu4hHS653En5h8EEEAAAQQQQAABBBBAAAEEEEAAAQSyIEAANAuIQYvwhsIrv4KM8emkk06yTp062fr16238+PEWG3zUsHgNodeq7AcddFC5BYwUVFXyeofGlxv/XPm9IfQffPBBud0KvKpH6K5du9z2nTt3Rvd751G91q5dG92e6EG650lUHtsRQAABBBBAAAEEEEAAAQQQQAABBBBIVYAh8KmKZZhfQ+GnTZtmH374YYWS1MPy6quvtiuvvNKee+45txp7jx49XM9O9fxctGiRtW3b1u6++243b6dXgLcw0uTJk23+/PmmQOqgQYO83RV+KzDZu3dve/XVV12g9V//+pcdeeSRrvz33nvP1qxZ4+YE1fydsYHOOnXq2L777usCtD//+c+tZcuWNmbMGGvevHmFc2hDuufxLYyNCCCAAAIIIIAAAggggAACCCCAAAIIpCFAD9A00DI5xBsKX69ePd9iunTpYo899ph1797dBSQff/xxmzhxomk4ed++fV3ws1mzZuWOPeOMM+zkk092vToVJI3v1Vku83+eKNCq49QTVYHQO++80/72t79Z69at7dFHH7URI0a4nNOnT7fYIe8jR450QdCNGze6BY6WLFniV3x0W7rniRbAAwQQQAABBBBAAAEEEEAAAQQQQAABBDIQKIkEt8oyOJ5Dq1BAw88///xzq1+/vnkLJCU7nYata/i8emnWrl07WdboPg2pX758uQueamEm9fIMknQerR5fWloaJLsbup/OeQIVHiDTD3/4Q3vxxRddzk8//dQ6duwY4CiyIIAAAskFpk6d6v4ApVxDhw61++67L/kB7EUAAQQCCnTr1s1mz57tcn/99dfWoEGDgEeSDQEEEEAAAQQQQCBegCHw8SIheq5gpOYEDZoU9Nx///2DZnf5GjdubIcddlhKxyizgqyppHTPk8o5lFfxfL+Yfuw2LRYVdMGoVM9PfgQQqHoB9aTXT66T330jdpvuM7HPc10/zocAApkLeAs+Zl5S8BL47BLcipwI5KtAdX12yVcv6o0AAghUhQA9QKtClTKrTeDWW2+1J554wvf86rWqHxICCOS3wAUXXGCaHiSXadmyZdanT5+Ep1TP8tg/tCTMyA4EEAi1wOrVq22//fbLaR0vvfRSe/31133PqQUuNQ0SCQEE8lvg2muvtbFjx+Z3I6g9AgggkOcC9ADN8wtI9YMLaAGpfAqA1qxZM9rTdseOHfbVV18Fb2wR5lQP6KZNm7qWa25bTe9ASiygRcq8KSw0tFI/pPQFWrRo4RaQS7+E3B6pa6/XgNK6devouVoJv+4t3tQyWhyQYHdyMI0S0f9hcopdTDH5Uez1E+jQoUN0GLzf/rBt4//i1K4I/xen5qVpwTSqTEmf8/R5j4QAAggggEBQAQKgQaXIlxcCCkLoy4JfUo8OBRLzJemL4549e1x1NWxGC1SREgvEeilYoS/fpMQCGqrtDdfON6/qeC/oS32ie4uUNQfzihUrEoOHbI/uLV4QT8Gq6phSIGQkSauze/fu6H68ohQJH8R66f/lfEqa3zzXSdMXJbq/aF8+fXbJ5/9bcn3ddb5YLy1yWh1TMFRHu9M9Zz57tWzZMt1mcxwCCCCAQJYEGAKfJUiKQSDbAosXL7bTTz/dFdu7d28WV6kE+P3337fzzz/f5erfv7/ddtttlRxR3Ltffvllu/zyyx3CJZdcYldccUVxgxRZ6wcPHmzTpk1zrX711VdNPeRJiQXOPfdcmzt3rsswa9Ysa9SoUeLM7LFevXrZypUrXS/jOXPmIFJEAjNnzrSBAwe6Fg8YMMBGjRpVRK1PvamTJ0+2q666yh142WWX2fDhw1MvpIiOePTRR2306NGuxbfccov99Kc/LaLW01QEEEAAgUwFamRaAMcjgAACCCCAAAIIIIAAAggggAACCCCAAAJhFSAAGtYrQ70QQAABBBBAAAEEEEAAAQQQQAABBBBAIGMBAqAZE+ZPAS+88IINGjTIJk2aVK7SGm6j7bELBPltK3dQFp7onPrZunVrFkqjCAQQQAABBBBAAAEEEEAAAQQQQAABBCoK5H6m94p1YEuOBLTS78KFC+2II44od8ZPPvnEBSFjFy3w21buoCw8UV2UvIV+slAkRSCAAAIIIIAAAggggAACCCCAAAIIIFBOgABoOY7ifHL22Wfbzp07rUGDBsUJENJWN2zY0L773e+62nXu3DmktQxPtUpLS6NehxxySHgqFtKaNG/ePOp10EEHhbSWVKuqBLp27epWH1b59erVq6rTFEy5xxxzjDVt2tS1pzpWCc83yO7du9uGDRusTp06+VZ16puhwD777BP9v6Vjx44Zllb4h7do0SLq1a5du8JvcIYtbN26ddSrVatWGZbG4QgggAACxSbAKvBFdMUfeeQRmzBhgvXr1y+6+nOi5vft29f1Cn3mmWesZcuWibJltN0L7r300kvWuHHjjMriYAQQQAABBBBAAAEEEEAAAQQQQAABBPwE6AHqp1Jk2z7//HPXE+jAAw+0ynq2aLj60qVLnZCClupFFpv27t1ry5Yts3//+99uaHunTp2sbdu2VrNmzdhsFR7HlpuoHipbdVU6+OCDK5TBBgQQQAABBBBAAAEEEEAAAQQQQAABBOIFCIDGixTh88GDBwfq7akA5G233WavvfaaadjJPffcU07rs88+s1tvvdUWLVpUbruClTfffLMlGwpVo0YNu+6662zFihU2atQoO+WUU8qVoSfvvfee/fKXv7QuXbrY/fffX2E/GxBAAAEEEEAAAQQQQAABBBBAAAEEEIgXYBX4eBGe+woo+Dl69GgX/FQPzXHjxpUbGj9//ny3oruCn9/73vdcwPOWW26x0047zRQYVZDVW/TI7wQlJSV2+umnu11///vf/bLYyy+/7LZ7+XwzsREBBBBAAAEEEEAAAQQQQAABBBBAAIEYAQKgMRg89BcoKyuzMWPG2CuvvGJaLEXBT03a7iXtv+uuu9xCSj//+c9dL9FTTz3V+vTpYzfeeKMNGzbMdu3a5fJ4x/j9VmBTgdB33nnHNm7cWC7L1q1b7a233nILKvj1Di2XmScIIIAAAggggAACCCCAAAIIIIAAAgj8R4AAKC+FpALq+Tl27FibMmWKG8L+xz/+0Zo1a1bumNmzZ9vHH3/s5gO98MILy+3Tk7POOssFLufOnWvz5s2rsN/boMWWvvOd77i5Q9944w1vs/v95ptvugCrFk5q1KhRuX25erJ7927bsWNHrk7HeRBAoIgE9EceEgIIIJBtAT67ZFuU8hBAAAEEEEAgXwUIgObrlctRvdWzc/Lkye5sV199te2zzz4VzrxkyRK37YADDrA5c+aYAqKxPxr67i1a5C1iVKGQ/2w444wz3CP1No1N1TX8/YMPPnDzmv73f/+39e7d2/Vq/dGPfmTXX3990mBubN2r+rEWncpFGjRokJvmwC9Qo2kOvP3vv/9+0up8+eWX0bz6YlZVyatPbH1fffVVd+4JEyZkdNpslZNOJTQVhdqmOgRNw4cPd8esX78+6CG++bJVjm/hRbZRvdwnTZpkF198sanHfN++fd3viy66yP785z+7eZmrm0SL02le5qpOL7zwgnt9ysMv3X333W6/plXRH+WSpUcffdTl/etf/5osW0b7/OqbzXtCdb3P9EdK3Vt0/qApW+3OVjlB613o+fjs8u0V9vss4O3Nl88u2bonVNf7LJ17i65RttqdrXK81w2/EUAAAQTyV4BFkPL32uWk5jNmzLC6deu6no/q/XnvvfdWWNHdC8B99NFHNmLEiKT1Wr58edL9PXv2tIYNG7oepcrbunVrW716tf3rX/9yPUyPPfbYpMdna+fXX3/thv1PnTo1WqSG/WuxpjVr1tjatWvt7bffdr1btTCThu7nOik48ac//cn0RT/RvKnZrJM3h6vOG5+2bdsWneP19ttvt8cee8xdx/h8eq6gp1eW3/5sbfPOEVvfDRs2uHN36NAho9Nkq5x0KqE/IqhtqkPQ9Mknn7iAWqYB52yVE7TehZpP91UtKLd582bXxHr16pnmVl63bp1bRE5zKT/11FP2hz/8IenicVXps2DBAncP1JQjP/vZz6ryVK7dek0fccQRvufR/zHar5+uXbta//79ffNp46pVq1y+7t27J8yT6Q5dp/j6ZvOeUF3vM/2/p3Y1aNAgMFG22p2tcgJXvEAz8tml4oXVa1op9rOAlytfPrtk655QXe+zdO4tukbZane2yvFeN/xGAAEEEMhfAQKg+XvtclJzfSFVr5shQ4a4oKR66Jx//vm+5z7mmGPsxBNP9N3nbTzkkEO8h76/FWzVF271sFEvUM0p6vX+VA+pmjVr+h6XzY2ar1R/Lf7000+ttLTU1UE9UxWkUNIHuWeeecYeeeQRV8/69evbZZddls0qBCpry5YtNnHiRKtVK1xvYwWIx48fb9dee22gduQyk15/5557rnXu3DmXp632c5199tluColUAhvVXukCrYCm99A9Vemkk05y95dOnTpFW6te9Pfcc48LRF155ZV2//33uz8ERTPk6IGmPVEgNmxzLj/wwAN2/PHHW5s2bXIkEew0xXpvKdZ2B3tV5DYXn10y8w7zZ5di/T+8WNud2SuZoxFAAAEEkgmEK3KSrKbsqxaBkSNHutXeNfz9hhtucEE/BTm1GJKX1HNJScGVH//4x97mtH8r2KgAqHpfKgCq+T+VcrX6+4MPPuiCnzrnqFGjLL7XqXqoDhw40E0H8Lvf/c7+8pe/mD6keQ46rliTesJqUay//e1v1qtXL6vKXljpGCtIr59iS5deemmxNTmU7dUX7DvuuMPV7eijj7bf/OY3rld5bGWPPPJI1/Nz6NChtnTpUnfPvemmm2KzFO1j9cDXPMyaBkKL8el5WFKx3luKtd1hed3F1oPPLrEaqT0O+2eXYv0/vFjbndqrl9wIIIAAAqkIhOfbQyq1Jm/OBLwel1p86OSTT3a9yPTlM3YokTe/54cfflhh9XZVdPv27TZ48GDXi1TzUlWWunTpYu3atTPNzaT5JNULST32tK2qk4akqnenknq6xgc/Y8+voKfaroBfoiHoGio5c+ZMF9CdNWuWr4/KE5PQ1gAAInlJREFU/Oqrr1x7vSGx6mWqtmv+VQ1FVc+O2KRyvflUdX5Z6cebH0/zC+q5ytOxqsM///lPd/1iy/GGo6uXreaG0jGZDJNu0qSJnXnmme4UWjxL7UgnBXVLtWzPWeV7ydsW1N47LtFvle1dj9j3SaL8udiu10r8tdXcvQqwKek1pDzq9fePf/zDDUlOpV5qp9fmWNtUyiiGvLq3qOe23ic333xzwgBe48aN3VyMMtH18F6bsUapvHdTudbetdy0aZM7nYZM6trqt1LQe4vyZvt9rPmX69SpY5pu5emnn9YpUk6puKVSuHcfiX/9p2Jf2fm8a6PrEX+eyo6tqv1+7fa2ea/byv4/q6xuaqt3fwnLPbWyOud6v6wL4bOLrrP3/9LKlSvdCCC/eYiz/T4O+2cXv//Di+F95tfuQr+n5vrewfkQQACBYhOgB2ixXfEM2nvFFVe4oNz8+fPd4h3eUHj1AFFvJs3Tqd5N+mKvoexe0hBOHaOh4oceeqi3Oelv9QK977777Pe//73Ld9pppyXNn62d6m2qD9bqzaqJ8ytL6sGldjVv3rxcVn0Z0fyc//d//xcNSiqDeiz95Cc/cQuf6Iu8lxR40rBxzSeqgLEeKyjlJfUu/fWvfx2dD1ALfTz//PNut74QXnjhhe6xpg1Q3dUDU71B1HNXZX/88cduvxaxevbZZ10QQUFRDbX15nD1ztW2bVu78cYb0x4mrukD3nvvPTdXquaNve6667yiK/2dqlulBcZlUKBXPcf0+tJCVkqp2scVWe6pnDVsWQsv6fWjnsJhSPoDhOqkL8gtW7Z0VdI2vXYfeugh9zrRF8/YpHkftUCP90eQ2H2xjxV013yWr732mrVq1cq9pmL38/gbAb2fZaSke6fmFE6WNB+yhntriHH8NBepvndTudYKfHr3E9VPrxn9qHe/pvoIcm+pqvex7oNqi97Dur9pKLzuV0FTqm5By1U+v3uLtqdir/yJUljfZ37tLoZ7aqLrVF3bC+Wzi0b9NGvWzC6//HJTz3fvj7rDhg1zn53kW1Xv4zB/dtF9JP7/8GJ4n/m1u9DvqdV1D+G8CCCAQLEIEAAtliudhXbqQ6k+IKoH6MMPP2wnnHBCdHX3q666yn05fuutt0yrGGuYvL60q/eS/lqr4UUKhGn4eJCk+T715V/Budq1a7vV14Mcl2kezb+npCH+8UEHv7L9hr0r0KGpA9Tbdd9993ULdiifHNRr6YknnnABSQUf4xdPUnBSgSjNu6egshZbUlBTDr/61a/ccHsFpNQbVwEUBVkVVPXmII0Nqqq+Wkjliy++cNdJQ0cVgFae2bNn2zXXXOOapNXtdS1Vb12/6dOn2yWXXGJ33nln0h6wfh7apmus+T8VzFUP1l6RofD/9V//lSh7dHsmbtFCMngQ1D7RKdRTV+8DfUnRsK0BAwYkyhqa7VoAQtda9gp2KkCu162+TD/++ON2wAEH2A9/+MOE9dWXU90PFNjTa1yrdVcW2EtYWIHvUG8mvZ+V2rdvX2lr9T73m6s23fdu0GutP6BoMbupkSlIdD9UkPG4445zgdjYSie6t1T1+1gLIE2bNs31AtWCa/pjUZCh8Om6xbY53cdB7ROVn6/vs2K8pya6hlW9vZA+u+j9ohEk+qyi+ZG1iJH3GaIq38d8duGzS1W/TykfAQQQQKD6BQiAVv81yKsaaB5ODZVWDz8FPtS7U1/UNRRcARP12FTQU1+OvaQPsPqLrfcB1tue7LcCh8qv1ZK1UIiGhOYirV+/3p1GAdB0k770KYik3nDyadq0qStKPbrkJwv1ln3ppZeiw8W9cyn4qeBhbNBJQ8ovigSVNX+ghsX36NHDunXrZlrJ3AuAJloVWcFPBTO8/QqCKkCna6cU26tCz9XTVos7TZgwwQVA1dM0PqiqfJUl1fEHP/iBvfjii/bb3/7WrQrfqFGjpIdl4pa04IA7g9r7FacvaAp+aqineq7069fPL1votumLpnov65p7i3ydc8457n383HPPuesX+1qMbYACXWPGjHEBer1fFPzUH0lI/gKxQ5a9aUP8cybemsl7N+i1Vu993S9071BQRQvhefeP2Jr53Vu0v6rfxwp2qve27olz5851fxRSr/pkKRO3ZOUG3RfU3q+8fH6fFeM91e8a5mJbIX12UQ/y/fff332O1OcGfW7RfSkX72M+u/DZJRfvV86BAAIIIFB9AswBWn32OT+zhhapd58CNLFJPQy13Rsaq31+27xjFORUfgXfYofHKvihobAKkCoYqiHsGqat4Ipf8FNl6CdRcNPrganhyrlKmlNJKdYi1XNr2LuShkB7wU+vDPWO03VQmjRpkrc5+ltBUwUOY5O2dezY0W1SL7JUkgLJscE4fYl45513bNWqVW7oqF9gQ8Nf1fNPAQ4Fs9NN6pW63377uV5vGgpfWcrErbKyg+xP1/7TTz91w971pU29amO9g5y3uvPoenvBT68uCtYrJXq9qUeaeuhoCJ5em7q+BD89Pf/f3pya6vUdP2WG/xEVt2b63k3nWlesxTdb/O4t2pOL97F6Gw8ZMsRVRP8PeXMGflOziv9m6laxxNS3pGOf7++zYr2npv7qyPyIQvvscsEFF5j3R1NvSqVcvY/57JL56zEXJRTjPTUXrpwDAQQQKHQBAqCFfoWroX0KXKpHWNeuXd0Q8HSq8OWXX7renwqg5XIl8dLSUlddv0n3g7RD84d6c2omqre3XQHG+AUd9MU+fli8zusFZOMXQ6qsTn7laSi+khZ4ig1gu42Rf3T9vJXSNQF9uknDyTRsX0m9XbUIU6KUqVuiclPZ7mel45PZy0dz4yr4qWHCZ511ViqnDEVevzkU9b5T0nXxS3fddZeb3kD7NM+shs6TkgtokQ0l9ehbvXp18swJ9mb63k3nWieoipvyIP5elcv3sf7QoN6pO3fudD3aFSxMlDJ1S1RuKtvTsc/391mx3lNTeV1kK2+hfXbxe7/k6n3MZ5dsvSqrthy/1wifXarWnNIRQACBQhAgAFoIV7FA2qDVkRV4VI+6W2+91QVfzj333EDzu2WLQL2alLwP2qmWq/orqKnFZbwvJPFlqBeoAo8KFsQHQrzzxx/j9YaN317Zc/XAiU9eUFO9PBMl7zgFaTNJCvZ6Q6g1FF6BQr+UqZtfmaluS8d+3rx5blVvzVOraSE0ZUO+Jb92qz1KCtb5JbXT65Wj3p/xgXy/Y4p9W2yvTw0NTidl+t5N51onqqd3j4jdn8v3sYbC33DDDe51qPdh7LQrsXXS40zd4stL53k69vn+PvNrs+yS/X9WCPfUdF4fmR7jWfPZ5ZvPPHx2Kfz3mfeaj33v8NklVoPHCCCAAAJ+AgRA/VTYVi0CGpatlYY1RHzWrFkJ556rysodeeSRrnh9iUjWo8irgxYN0mI/3pdv74udAkKJgkfa5wWM4ntgBlnMwzt3kN9+83d6dUzUu0/las4tpfj6uY0p/uMNJ9MciFr4yS95dUrXza/MVLelYy+fm2++2X7xi1+40yUL8qZan1zlT6fd6nk3ceJE18NbK9/7TeeQq/rny3n0BwcvCBo0SKH5gDXlyL///W/XTO99ku57N51rncg32b0lV+/jNm3aRIfCP/TQQ9FAZ3ydM3WLLy+d5+nY5/v7LJ02F8I9NZ3XR6bH8NnlG0E+uwR7JRXC+yyd+0u+31ODXV1yIYAAAggkEyAAmkyHfTkV0KT3hx12mLVu3doNJdZCPd5fc3NVEa1er6QP0VrIqLKkVc41L9WHH37osmq4tD5Yaljmhg0bfA+P7fVZHUOHFTRQSjS/o/YpGK0UP4ep25jiP1pV+rrrrnNHvfzyy769JPPBza/Zffr0sVNOOcXOO+88O/TQQ00LUWgxoEJPI0eOdFMDaPi7kub5DRrUK3SbRO3TcHEt6KYUpKfwggUL3LQRWozKS7l+73rnDfq7Ot7HGgqv4I83FN7741JsncPuFlvX2MfF+D4r1ntq7HVP5zGfXb5R47NLsFdPsb7PivGeGuwVQS4EEECgeAQIgBbPtQ59SzXhvRa0UG8yLSZTHcFBDanp27evsxo3bpxbdTQRnBZw8gIZZ599tsum4KfmP1V6/fXX3e/4f7zthx9+eHQYcXyeIM+9v34n6mmaqIz27du7XVrgyOstEZtXUxHMnDnTbTr66KNjd6X9OHZ+zPHjx1coJ5duFU6ewQbVW0m/FeTVby0glsniURlUJ2eHeu3+7ne/ayeffHLS4FPOKpUHJ1KwTnZaXV1/DEiUNNev5n9U6ty5c3QRtFy+d737S5Ce8F471LZc3f+8cyqwrFXhNSWDeiNPnTrV2xX9nUu36Emz8KAY32dem/W7mO6pmb5c+OxibjoaPrsEeyUV6/vMazefXYK9TsiFAAIIFKIAAdBCvKq0KSOBoUOHmibBX7RokQ0bNszefffdcoFCBQRefPFF+9///V93nl69epVbqMlb5f3xxx+PDl31KqReXU8++aR7mulq4d4cjOrxtHbtWu8Ulf5WL7ROnTq53ooKRsb2mNLQWg1T11ydCmRooaRsJVmqh9i2bdt8i8yVm+/Js7BRq6Gff/75rqQ77rgj4XynWThVqIrQIlCNGze2+fPnMxS+kivTrl07N82HsqmH+4QJE2z58uXljtI8mgroaS5EDTMfMWJEdH8u37ve/cXrURWtRCUPquN9HDsU3u/+kku3SnjS3l2M77Nivaem+yLhswufXdJ57RTr+6wY76npvD44BgEEECg0gVqF1iDag0CmApqnT8OYNben5t7TMF8FIo466ii3INPixYujAUfNJ6QhNbGrIffs2dP1invzzTfd/HQaIq3VcLUQh3p/KsiooMb3v//9jKqqOqnXh4ZdK+ig4OKYMWOi8wwmKlw9u9SmK6+80jS8VoGWHj16uDlP1XtCgV+trikDb+68RGWlst0bCq/z+qVcufmdO1vbBg4caFMjPdCWLl3qevDddNNN2Sq6QjkKXt93330VtnsbdE3Hjh3rPa2y382aNbPhw4e7gN7DDz9sJ5xwgh188MFVdr58L3jIkCGup9ILL7zgpg7Q9AFaUEhTKGhaCt1zdI9QT5VbbrnFunTpEm1yLt+73iJHmuZDwW0FEQcNGhStS6IH1fU+1h+Upk2bFp2OJLZ+uXSLPW82H+fyfbZ161bTH/aSJd17NIqhqlMu76lV3ZaqLp/PLnx2Sfc1lqv3WZjuLbm8p6Z7XTgOAQQQQCD7AvQAzb4pJRaAgIIRCkwMGDDA9W7T/HJa5Vvzfaq3peYr1fA8rYDt9ZSKbfavf/1rF2RU0G/KlCn24IMPuuCnvjDquP79+8dmT/uxgq8Kgm7cuNEWLlwYeB5GBVUee+wx13NVAU/1VtWiNps2bXJTACj4qQ+H2U7qUXrWWWclLDZXbgkrkOEOBaV/9atfuVL+/ve/29tvv51hiYkP19QH6r2b7Cfx0dndc/rpp5umOdDQbfVsjO1VnN0z5X9pCsZpig/1INcfVZTU61N/MFEPcV1Xzc+m96OCifEpV+/dM844w/0hR4FY3SOCzIns1bU63sfeUPh69ep51Sj3O1du5U6a5Se5fJ8lu69oX6pTr6RLkct7arp1DNNxfHbhs0s6r8dcvs/Ccm+RUy7vqelcF45BAAEEEMi+QEnkQ2xZ9oulRAQKR0Af1tTL0htmrt6cTZo0CdxArX6uhY86dOhgib6cBy4sQUbVT701S0tLE+RIvFnBXfVOrV+/vnmLhSTOnbs9uXDLXWs4EwL+AuoRo/uD/oihHlxaLT5oz+tcvHcV1Nb9RX9oSWdRujC+j3Ph5n+12YpA7gT47JI769gzhfGeF1s/HiOAAAIIIFDMAgRAi/nq03YEEEAAAQQQQAABBBBAAAEEEEAAAQQKXIAh8AV+gWkeAggggAACCCCAAAIIIIAAAggggAACxSxAALSYrz5tRwABBBBAAAEEEEAAAQQQQAABBBBAoMAFCIAW+AWmeQgggAACCCCAAAIIIIAAAggggAACCBSzAAHQYr76tB0BBBBAAAEEEEAAAQQQQAABBBBAAIECFyAAWuAXmOYhgAACCCCAAAIIIIAAAggggAACCCBQzAIEQIv56tN2BBBAAAEEEEAAAQQQQAABBBBAAAEEClyAAGiBX2CahwACCCCAAAIIIIAAAggggAACCCCAQDELEAAt5qtP2xFAAAEEEEAAAQQQQAABBBBAAAEEEChwAQKgBX6BaR4CCCCAAAIIIIAAAggggAACCCCAAALFLFCrmBtP2xFAAAEEEEAg+wJffvmlLVmyxJYuXWoNGza0Dh06WNu2ba1mzZrZPxklIoAAAggggAACCCCAAAKVCNADtBIgdiOAAAIIIIBA5QLbt2+3xx57zHr27GnNmjWzbt262TnnnGOnnnqqtW/f3gVCL730Ulu2bFnlhYU8h9pZUlLifmbPnl2utr/85S+j+3bu3Flun/dkxowZ3sPo782bN0ePu+GGG6LbeYAAAggggAACCCCAAAKZCxAAzdyQEhBAAAEEEChqgQULFtixxx5rAwcOtOnTp/ta7Nixw+677z7r2LGjPfDAA755CmFjWVlZwmasXr3afvazn9kpp5ySMA87EEAAAQQQQAABBBBAIPsCBECzb0qJCCCAAAIIFI3Aa6+9Zscdd5zNmzfPtblLly728MMP2wcffGAbNmxww+CV57zzznM9HNUr8pJLLrE///nPBWlUu3Ztq1evnvuJb+CoUaNcu/2CpOpR6h1XqxYzFMXb8RwBBBBAAAEEEEAAgUwESiIfwhN3VcikZI5FAAEEEEAAgYIWWLt2rR1xxBGmno1Kv/3tb80bAu7X8Oeff9769etne/bsMQX5FDQ95JBD/LKGepuGwKu3q5ICvcccc0yg+irwe//991vdunVNUwaQEEAAAQQQQAABBBBAIDcC9ADNjTNnQQABBBBAoOAEFNDzgp+/+c1v7JprrnG9PBM1VHOC3nbbbW737t277Q9/+EOirGxHAAEEEEAAAQQQQAABBLImwBirrFFSEAIIIIAAAsUjsHz5cnvuuedcgw866CAX/AzS+uHDh7ueolopfsqUKa4npIZ+xyf1Ep01a5Z9/PHHtnjxYreK/JFHHul6nNavXz8+u3vuHaMnhx9+uDVu3NgUaJ0zZ47985//tE2bNrnFmb7zne9Y8+bNfcuI3Thz5kx7//33bd26daZjTjzxRLfAU2ye+Mda5GnlypVus6YG0ND2FStW2BdffGFr1qxx2zX45t1333WP999/f9e2vXv3unNpY6tWraxNmzZuf/w/Xhur0yW+TjxHAAEEEEAAAQQQQCDsAgRAw36FqB8CCCCAAAIhFJg0aZIpaKc0dOhQ09yXQVLDhg3txRdftH333dcOPfRQ30PeeOMNu/zyy23u3LkV9itwee+991r//v0r7NNK6j169HDb33zzTVens88+29avX18urwKud999tw0ePLjcdu/JwoUL7aKLLjIFQGNTjRo17M4770waBL3rrrvs97//vTtMCz/VqVPHJkyYYCNHjowWpXlQvXpeccUVrifs119/Hd12/fXX2+jRo6P5vQfV7eLVg98IIIAAAggggAACCOSbAEPg8+2KUV8EEEAAAQRCIPDSSy9Fa6GemamkE044IWHwU8FNrZKu4GfNmjXd/JpaOf2kk04y9fxUb0wtqPQ///M/SU85efJkO/XUU13wUyvP9+nTJ9rrU/NvDhkyxAVB4wtRb1H19PSCnwrSnn/++e78CvJeeeWVNnbs2PjDkj4/4IAD7Nhjj7UWLVq4fOoVquf6OfDAA5Me6+2sbhevHvxGAAEEEEAAAQQQQCAvBbQIEgkBBBBAAAEEEEhFILJ4kRZRdD9LlixJ5dCEeT/55JOyBg0auDLbtWtXFglClsur83Tv3j163ieffLLc/siw+ug+1S0yNL8s0hM0mifSY7Us0hszmufggw8uiwwpL7c/0jPT7Y8s0lQ2bty46D49iAw7L4sEU6PH6xyRRZDK5bnqqqui+yM9QMvti/SUdfsiiyCV264nkeH50eMiPUDL7a9ul3KV4QkCCCCAAAIIIIAAAnkoQA/QvAxbU2kEEEAAAQSqV0BzgCppSHvbtm2zUhkNO9+6davr+an5Qb1h4l7hkaCovf7669ayZUu3KRJsNA17T5Q09LxXr17R3ep5qXN4K7h/9tln9tFHH0X3a4j5O++8455rrtJhw4ZF9+mB5hVVz1INhc9lqm6XXLaVcyGAAAIIIIAAAgggUBUCuf0EXxUtoEwEEEAAAQQQyKmAFuLRnJVKGtatwGKmaePGjTZjxgxXzAUXXOCCjX5lNmrUyG688Ua3S4sNKSDql7QAUWzwMzbPUUcdFX26du3a6GMtuqQU6f1pV199dXR77INIz1ff+Udj82TzcRhcstkeykIAAQQQQAABBBBAoDoECIBWhzrnRAABBBBAII8FNDdns2bNXAu06rnm1Mw0zZ8/P1qE5utMljS3p5e0YJFfat++vd9mty0yND66b9euXdHHH374oXusnqatW7eObo9/UFn94vNn8jwMLpnUn2MRQAABBBBAAAEEEAiDAAHQMFwF6oAAAggggECeCey///6uxuoNumDBgoxrHxvoiw1Q+hWs/V6v00QB0GTD8rWYkpe8lez13AuAtmnTxtvt+zvowkW+B6e4MQwuKVaZ7AgggAACCCCAAAIIhE6AAGjoLgkVQgABBBBAIPwChx12WLSSkcWBoo+DPND8ofPmzbPI3OnR7CtWrIg+9lZLj26Ie1CvXj23Irw2r1+/Pm7vN0+VJ9W0aNEid4jXuzXR8V7wN9H+bG4Pg0s220NZCCCAAAIIIIAAAghUhwAB0OpQ55wIIIAAAgjkucAPfvCDaAsUzEwl3XHHHda1a1e3mNFLL73kDtWwcy95Cyx5z+N/R1Z7d4slaXvz5s3jd6f9fN9993XHxgYd/QpLFHT1y5vptjC4ZNoGjkcAAQQQQAABBBBAoLoFCIBW9xXg/AgggAACCOShgAKg3mroTz31lO3cuTNQKzRkftKkSS7vpk2brHv37u5xp06doscvWbIk+tjvQex+b0V4v3ypbvOGtn/++edJD61sf9KDU9wZBpcUq0x2BBBAAAEEEEAAAQRCJ0AANHSXhAohgAACCCAQfgENUx84cKCrqIaO/+53vwtU6ZtuuslWr17t8p577rnRHpxaXd2b1/PJJ59MWtYTTzwR3Z9opfdohhQenHbaaS73qlWr7O2330545CuvvJJwX7IdXvtih/4ny699YXCprI7sRwABBBBAAAEEEEAg7AIEQMN+hagfAggggAACIRUYM2aMlZaWutqNHDnS9DxZeuCBB+z22293WbQQ0bXXXhvNrnk3L7roIvf8tddes0RBRvW+HD9+vMunIGzv3r2jZWT6YMCAAVa3bl1XjNoTu0CSV/acOXPs6aef9p6m9Nubl1S9Zbds2RLo2DC4BKoomRBAAAEEEEAAAQQQCLEAAdAQXxyqhgACCCCAQJgF9ttvP3v44Yetdu3abkGj66+/3rp162aPPPKIaWEkDXHXCvHPPvusnXjiiTZ06FDXHA2dVy/Oo446qlzzYgOq55xzjilgumPHDpdHwciXX37ZevToYdu2bXPbxo0bZ7Vq1SpXRiZP1NtSdVeaNm2aaZi/11tVvTZfffVV69Onj29gNMh5mzZtGs1266232vTp051TdGOCB9XtkqBabEYAAQQQQAABBBBAIG8ECIDmzaWioggggAACCIRPQMPYtZBR48aNXeVmz55tF198sXXp0sX1Dj388MOtX79+NmPGDLdf+R588EFTgDM+KaA6ceJENyx++/btLmDapEkTt2CSepqefvrpLiCpAOro0aPtvPPOiy8i4+c//elP7eabb3blTJkyxbTiuwKjWmzp+9//vm3YsMFGjBiR1nm+973vRYf5a8qAnj17moLGlaUwuFRWR/YjgAACCCCAAAIIIBBmAQKgYb461A0BBBBAAIE8EFCvSM0Detttt1mbNm18a9ywYUO7/PLLXT4FSBOlM88807SqfP/+/a1BgwZucSU915BxBT779u1rb775ZqDAYaJzVLZ91KhRbji/htgrffrppy7w2apVK7eAkzf3aWXlxO9XwFO9VlWOl+bPn+89TPo7DC5JK8hOBBBAAAEEEEAAAQRCLFASGdJVFuL6UTUEEEAAAQQQyCMBfazQsPFly5bZF1984XqBqgdl69ato70fgzZHw94VWNUweg0f14ro2Vz1vbJ6aPi9hvIvX77c9UI96KCDKjsk8P6VK1fa1q1bXcDYm3c06MHV7RK0nuRDAAEEEEAAAQQQQCAsAgRAw3IlqAcCCCCAAAIIIIAAAggggAACCCCAAAIIZF2AIfBZJ6VABBBAAAEEEEAAAQQQQAABBBBAAAEEEAiLAAHQsFwJ6oEAAggggAACCCCAAAIIIIAAAggggAACWRcgAJp1UgpEAAEEEEAAAQQQQAABBBBAAAEEEEAAgbAIEAANy5WgHggggAACCCCAAAIIIIAAAggggAACCCCQdQECoFknpUAEEEAAAQQQQAABBBBAAAEEEEAAAQQQCIsAAdCwXAnqgQACCCCAAAIIIIAAAggggAACCCCAAAJZFyAAmnVSCkQAAQQQQAABBBBAAAEEEEAAAQQQQACBsAgQAA3LlaAeCCCAAAIIIIAAAggggAACCCCAAAIIIJB1AQKgWSelQAQQQAABBBBAAAEEEEAAAQQQQAABBBAIiwAB0LBcCeqBAAIIIIAAAggggAACCCCAAAIIIIAAAlkXIACadVIKRAABBBBAAAEEEEAAAQQQQAABBBBAAIGwCBAADcuVoB4IIIAAAggggAACCCCAAAIIIIAAAgggkHUBAqBZJ6VABBBAAAEEEEAAAQQQQAABBBBAAAEEEAiLAAHQsFwJ6oEAAggggAACCCCAAAIIIIAAAggggAACWRcgAJp1UgpEAAEEEEAAAQQQQAABBBBAAAEEEEAAgbAIEAANy5WgHggggAACCCCAAAIIIIAAAggggAACCCCQdQECoFknpUAEEEAAAQQQQAABBBBAAAEEEEAAAQQQCIsAAdCwXAnqgQACCCCAAAIIIIAAAggggAACCCCAAAJZFyAAmnVSCkQAAQQQQAABBBBAAAEEEEAAAQQQQACBsAgQAA3LlaAeCCCAAAIIIIAAAggggAACCCCAAAIIIJB1AQKgWSelQAQQQAABBBBAAAEEEEAAAQQQQAABBBAIiwAB0LBcCeqBAAIIIIAAAggggAACCCCAAAIIIIAAAlkXIACadVIKRAABBBBAAAEEEEAAAQQQQAABBBBAAIGwCBAADcuVoB4IIIAAAggggAACCCCAAAIIIIAAAgggkHUBAqBZJ6VABBBAAAEEEEAAAQQQQAABBBBAAAEEEAiLAAHQsFwJ6oEAAggggAACCCCAAAIIIIAAAggggAACWRcgAJp1UgpEAAEEEEAAAQQQQAABBBBAAAEEEEAAgbAIEAANy5WgHggggAACCCCAAAIIIIAAAggggAACCCCQdQECoFknpUAEEEAAAQQQQAABBBBAAAEEEEAAAQQQCIsAAdCwXAnqgQACCCCAAAIIIIAAAggggAACCCCAAAJZFyAAmnVSCkQAAQQQQAABBBBAAAEEEEAAAQQQQACBsAgQAA3LlaAeCCCAAAIIIIAAAggggAACCCCAAAIIIJB1AQKgWSelQAQQQAABBBBAAAEEEEAAAQQQQAABBBAIi8D/A+Fqtww6K2tbAAAAAElFTkSuQmCC" width="672" /></p>
<pre class="r"><code>ggsave(&quot;TrustSha.pdf&quot;, final_plot, width = 7, height = 5)</code></pre>
</div>
</div>
<div id="descriptive-mean-sds-across-conditions" class="section level2">
<h2>Descriptive: Mean &amp; SDs across conditions</h2>
<pre class="r"><code>#Summary for Sharing:
# Control .92 (1.13)
# No link .87 (1.09)
# Link    .83 (1.09) 

#Summary for belief:
# Control 1.18 (1.08)
# No link 1.13 (1.09)
# Link    1.07 (1.07) 


table(corrections_accuracy_long$country, corrections_accuracy_long$condition)</code></pre>
<pre><code>##         
##          control correction link
##   Brazil    1304       1344 1352
##   India     1320       1340 1340
##   UK        1348       1284 1368</code></pre>
<pre class="r"><code>mean_accuracy_by_condition_Country &lt;- aggregate(accuracy ~ condition * country, corrections_accuracy_long, mean)
mean_accuracy_by_condition_Country</code></pre>
<pre><code>##    condition country  accuracy
## 1    control  Brazil 1.0337423
## 2 correction  Brazil 0.9508929
## 3       link  Brazil 0.9341716
## 4    control   India 1.6757576
## 5 correction   India 1.5992537
## 6       link   India 1.5119403
## 7    control      UK 0.8264095
## 8 correction      UK 0.8161994
## 9       link      UK 0.7558480</code></pre>
<pre class="r"><code>sd_accuracy_by_condition_Country &lt;- aggregate(accuracy ~ condition * country, corrections_accuracy_long, sd)
sd_accuracy_by_condition_Country</code></pre>
<pre><code>##    condition country  accuracy
## 1    control  Brazil 1.0210807
## 2 correction  Brazil 1.0154279
## 3       link  Brazil 1.0299516
## 4    control   India 1.1356863
## 5 correction   India 1.1554977
## 6       link   India 1.1558240
## 7    control      UK 0.8767304
## 8 correction      UK 0.9151973
## 9       link      UK 0.8774394</code></pre>
<pre class="r"><code>mean_sharing_by_condition_Country &lt;- aggregate(sharing ~ condition * country, corrections_sharing_long, mean)
mean_sharing_by_condition_Country</code></pre>
<pre><code>##    condition country   sharing
## 1    control  Brazil 0.7055215
## 2 correction  Brazil 0.5907738
## 3       link  Brazil 0.6353550
## 4    control   India 1.6090909
## 5 correction   India 1.5350746
## 6       link   India 1.4388060
## 7    control      UK 0.4658754
## 8 correction      UK 0.4571651
## 9       link      UK 0.4247076</code></pre>
<pre class="r"><code>sd_sharing_by_condition_Country &lt;- aggregate(sharing ~ condition * country, corrections_sharing_long, sd)
sd_sharing_by_condition_Country</code></pre>
<pre><code>##    condition country   sharing
## 1    control  Brazil 1.0083764
## 2 correction  Brazil 0.9257327
## 3       link  Brazil 0.9791422
## 4    control   India 1.1741113
## 5 correction   India 1.1866042
## 6       link   India 1.1716027
## 7    control      UK 0.8288731
## 8 correction      UK 0.8007421
## 9       link      UK 0.8079003</code></pre>
<pre class="r"><code>corrections_merged &lt;- corrections_merged %&gt;%
  mutate(mean_accuracy = rowMeans(select(., false_1_accuracy:false_4_accuracy), na.rm = TRUE))

mean_accuracy_by_condition_Country &lt;- aggregate(mean_accuracy ~ condition * country, corrections_merged, mean)
mean_accuracy_by_condition_Country</code></pre>
<pre><code>##    condition country mean_accuracy
## 1    control  Brazil     1.0337423
## 2 correction  Brazil     0.9508929
## 3       link  Brazil     0.9341716
## 4    control   India     1.6757576
## 5 correction   India     1.5992537
## 6       link   India     1.5119403
## 7    control      UK     0.8264095
## 8 correction      UK     0.8161994
## 9       link      UK     0.7558480</code></pre>
<pre class="r"><code>sd_accuracy_by_condition_Country &lt;- aggregate(mean_accuracy ~ condition * country, corrections_merged, sd)
sd_accuracy_by_condition_Country</code></pre>
<pre><code>##    condition country mean_accuracy
## 1    control  Brazil     0.6802236
## 2 correction  Brazil     0.6603137
## 3       link  Brazil     0.6502061
## 4    control   India     0.8450303
## 5 correction   India     0.8924371
## 6       link   India     0.8847548
## 7    control      UK     0.6503089
## 8 correction      UK     0.6904047
## 9       link      UK     0.6418638</code></pre>
<pre class="r"><code>N_by_condition_Country &lt;- aggregate(mean_accuracy ~ condition * country, corrections_merged, length)
N_by_condition_Country</code></pre>
<pre><code>##    condition country mean_accuracy
## 1    control  Brazil           326
## 2 correction  Brazil           336
## 3       link  Brazil           338
## 4    control   India           330
## 5 correction   India           335
## 6       link   India           335
## 7    control      UK           337
## 8 correction      UK           321
## 9       link      UK           342</code></pre>
</div>
<div id="quantifying-floor-effects" class="section level2">
<h2>Quantifying floor effects</h2>
<pre class="r"><code># Summary: we have very clear floor effects in the UK, and some floor effects in Brazil too. But no problem in India. 

# Percentage of zeros
Uk_share = filter(corrections_sharing_long, country ==&quot;UK&quot;)
table(Uk_share$sharing)</code></pre>
<pre><code>## 
##    0    1    2    3 
## 2879  597  373  151</code></pre>
<pre class="r"><code>2879/4000 #72%</code></pre>
<pre><code>## [1] 0.71975</code></pre>
<pre class="r"><code>Ind_share = filter(corrections_sharing_long, country ==&quot;India&quot;)
table(Ind_share$sharing)</code></pre>
<pre><code>## 
##    0    1    2    3 
## 1162  687 1031 1120</code></pre>
<pre class="r"><code>1162/4000 # 29%</code></pre>
<pre><code>## [1] 0.2905</code></pre>
<pre class="r"><code>Bra_share = filter(corrections_sharing_long, country ==&quot;Brazil&quot;)
table(Bra_share$sharing)</code></pre>
<pre><code>## 
##    0    1    2    3 
## 2546  647  495  312</code></pre>
<pre class="r"><code>2546/4000 #64%</code></pre>
<pre><code>## [1] 0.6365</code></pre>
<pre class="r"><code>Uk_belief = filter(corrections_accuracy_long, country ==&quot;UK&quot;)
table(Uk_belief$accuracy)</code></pre>
<pre><code>## 
##    0    1    2    3 
## 1885 1215  719  181</code></pre>
<pre class="r"><code>1885/4000 #47%</code></pre>
<pre><code>## [1] 0.47125</code></pre>
<pre class="r"><code>Ind_belief = filter(corrections_accuracy_long, country ==&quot;India&quot;)
table(Ind_belief$accuracy)</code></pre>
<pre><code>## 
##    0    1    2    3 
## 1013  746 1088 1153</code></pre>
<pre class="r"><code>1013/4000 #25%</code></pre>
<pre><code>## [1] 0.25325</code></pre>
<pre class="r"><code>Bra_belief = filter(corrections_accuracy_long, country ==&quot;Brazil&quot;)
table(Bra_belief$accuracy)</code></pre>
<pre><code>## 
##    0    1    2    3 
## 1723 1091  760  426</code></pre>
<pre class="r"><code>1723/4000 #43%</code></pre>
<pre><code>## [1] 0.43075</code></pre>
<pre class="r"><code># Percentage of zeros in the control condition
Uk_share = filter(corrections_sharing_long, country ==&quot;UK&quot; &amp; condition ==&quot;control&quot;)
table(Uk_share$sharing)</code></pre>
<pre><code>## 
##   0   1   2   3 
## 963 194 139  52</code></pre>
<pre class="r"><code>963/1348 #71%</code></pre>
<pre><code>## [1] 0.7143917</code></pre>
<pre class="r"><code>Ind_share = filter(corrections_sharing_long, country ==&quot;India&quot;&amp; condition ==&quot;control&quot;)
table(Ind_share$sharing)</code></pre>
<pre><code>## 
##   0   1   2   3 
## 347 227 341 405</code></pre>
<pre class="r"><code>347/1320 # 26%</code></pre>
<pre><code>## [1] 0.2628788</code></pre>
<pre class="r"><code>Bra_share = filter(corrections_sharing_long, country ==&quot;Brazil&quot;&amp; condition ==&quot;control&quot;)
table(Bra_share$sharing)</code></pre>
<pre><code>## 
##   0   1   2   3 
## 793 220 173 118</code></pre>
<pre class="r"><code>793/1304 #61%</code></pre>
<pre><code>## [1] 0.6081288</code></pre>
<pre class="r"><code>Uk_belief = filter(corrections_accuracy_long, country ==&quot;UK&quot;&amp; condition ==&quot;control&quot;)
table(Uk_belief$accuracy)</code></pre>
<pre><code>## 
##   0   1   2   3 
## 604 425 268  51</code></pre>
<pre class="r"><code>604/1348 #45%</code></pre>
<pre><code>## [1] 0.4480712</code></pre>
<pre class="r"><code>Ind_belief = filter(corrections_accuracy_long, country ==&quot;India&quot;&amp; condition ==&quot;control&quot;)
table(Ind_belief$accuracy)</code></pre>
<pre><code>## 
##   0   1   2   3 
## 294 252 362 412</code></pre>
<pre class="r"><code>294/1320 #22%</code></pre>
<pre><code>## [1] 0.2227273</code></pre>
<pre class="r"><code>Bra_belief = filter(corrections_accuracy_long, country ==&quot;Brazil&quot;&amp; condition ==&quot;control&quot;)
table(Bra_belief$accuracy)</code></pre>
<pre><code>## 
##   0   1   2   3 
## 514 376 270 144</code></pre>
<pre class="r"><code>514/1304 #39%</code></pre>
<pre><code>## [1] 0.3941718</code></pre>
</div>
<div id="individual-posts-uk---accuracy" class="section level2">
<h2>Individual posts UK - Accuracy</h2>
<div id="models-10" class="section level3">
<h3>Models</h3>
<pre class="r"><code>Post_1_UK &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;UK&quot;&amp; post==&quot;false_1_accuracy&quot;))
summ(Post_1_UK)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 1.86, p = 0.16
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.90   0.05    17.66   0.00
## conditioncorrection         -0.05   0.07    -0.62   0.53
## conditionlink               -0.14   0.07    -1.90   0.06
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_2_UK &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;UK&quot;&amp; post==&quot;false_2_accuracy&quot;))
summ(Post_2_UK)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.60, p = 0.55
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.55   0.05    11.94   0.00
## conditioncorrection          0.01   0.07     0.18   0.86
## conditionlink               -0.05   0.06    -0.85   0.40
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_3_UK &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;UK&quot;&amp; post==&quot;false_3_accuracy&quot;))
summ(Post_3_UK)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.03, p = 0.97
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.77   0.05    16.09   0.00
## conditioncorrection         -0.01   0.07    -0.22   0.83
## conditionlink               -0.00   0.07    -0.04   0.97
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_4_UK &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;UK&quot;&amp; post==&quot;false_4_accuracy&quot;))
summ(Post_4_UK)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 1.44, p = 0.24
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  1.09   0.04    24.35   0.00
## conditioncorrection          0.01   0.06     0.12   0.90
## conditionlink               -0.09   0.06    -1.41   0.16
## --------------------------------------------------------</code></pre>
</div>
<div id="plots-8" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>Post_1_UK_ &lt;- ggpredict(Post_1_UK, terms = c(&quot;condition&quot;))
Post_2_UK_ &lt;- ggpredict(Post_2_UK, terms = c(&quot;condition&quot;))
Post_3_UK_ &lt;- ggpredict(Post_3_UK, terms = c(&quot;condition&quot;))
Post_4_UK_ &lt;- ggpredict(Post_4_UK, terms = c(&quot;condition&quot;))

Post_1_UK_plot &lt;- ggplot(Post_1_UK_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK_Post_1&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_2_UK_plot &lt;- ggplot(Post_2_UK_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK_Post_2&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_3_UK_plot &lt;- ggplot(Post_3_UK_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK_Post_3&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_4_UK_plot &lt;- ggplot(Post_4_UK_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK_Post_4&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_1_UK_plot + Post_2_UK_plot + Post_3_UK_plot + Post_4_UK_plot</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
</div>
</div>
<div id="individual-posts-brazil---accuracy" class="section level2">
<h2>Individual posts Brazil - Accuracy</h2>
<div id="models-11" class="section level3">
<h3>Models</h3>
<pre class="r"><code>Post_1_Bra &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;Brazil&quot;&amp; post==&quot;false_1_accuracy&quot;))
summ(Post_1_Bra)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.70, p = 0.50
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  1.43   0.06    23.65   0.00
## conditioncorrection         -0.10   0.08    -1.17   0.24
## conditionlink               -0.04   0.08    -0.42   0.67
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_2_Bra &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;Brazil&quot;&amp; post==&quot;false_2_accuracy&quot;))
summ(Post_2_Bra)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.26, p = 0.77
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.90   0.05    17.79   0.00
## conditioncorrection         -0.02   0.07    -0.21   0.83
## conditionlink               -0.05   0.07    -0.70   0.48
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_3_Bra &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;Brazil&quot;&amp; post==&quot;false_3_accuracy&quot;))
summ(Post_3_Bra)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 2.37, p = 0.09
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.69   0.05    13.71   0.00
## conditioncorrection         -0.12   0.07    -1.72   0.09
## conditionlink               -0.14   0.07    -2.02   0.04
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_4_Bra &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;Brazil&quot;&amp; post==&quot;false_4_accuracy&quot;))
summ(Post_4_Bra)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 2.38, p = 0.09
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  1.11   0.06    19.98   0.00
## conditioncorrection         -0.10   0.08    -1.22   0.22
## conditionlink               -0.17   0.08    -2.18   0.03
## --------------------------------------------------------</code></pre>
</div>
<div id="plots-9" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>Post_1_Bra_ &lt;- ggpredict(Post_1_Bra, terms = c(&quot;condition&quot;))
Post_2_Bra_ &lt;- ggpredict(Post_2_Bra, terms = c(&quot;condition&quot;))
Post_3_Bra_ &lt;- ggpredict(Post_3_Bra, terms = c(&quot;condition&quot;))
Post_4_Bra_ &lt;- ggpredict(Post_4_Bra, terms = c(&quot;condition&quot;))

Post_1_Bra_plot &lt;- ggplot(Post_1_Bra_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Bra_Post_1&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_2_Bra_plot &lt;- ggplot(Post_2_Bra_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Bra_Post_2&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_3_Bra_plot &lt;- ggplot(Post_3_Bra_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Bra_Post_3&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_4_Bra_plot &lt;- ggplot(Post_4_Bra_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Bra_Post_4&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_1_Bra_plot + Post_2_Bra_plot + Post_3_Bra_plot + Post_4_Bra_plot</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
</div>
</div>
<div id="individual-posts-india---accuracy" class="section level2">
<h2>Individual posts India - Accuracy</h2>
<div id="models-12" class="section level3">
<h3>Models</h3>
<pre class="r"><code>Post_1_India &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;India&quot;&amp; post==&quot;false_1_accuracy&quot;))
summ(Post_1_India)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.45, p = 0.64
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  1.47   0.06    23.28   0.00
## conditioncorrection         -0.02   0.09    -0.25   0.81
## conditionlink               -0.08   0.09    -0.92   0.36
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_2_India &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;India&quot;&amp; post==&quot;false_2_accuracy&quot;))
summ(Post_2_India)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 2.45, p = 0.09
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  1.75   0.06    29.71   0.00
## conditioncorrection         -0.07   0.08    -0.82   0.41
## conditionlink               -0.18   0.08    -2.19   0.03
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_3_India &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;India&quot;&amp; post==&quot;false_3_accuracy&quot;))
summ(Post_3_India)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 1.60, p = 0.20
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  1.28   0.07    18.82   0.00
## conditioncorrection         -0.04   0.10    -0.45   0.65
## conditionlink               -0.17   0.10    -1.72   0.09
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_4_India &lt;- lm(accuracy ~ condition, data=subset(corrections_accuracy_long, country==&quot;India&quot;&amp; post==&quot;false_4_accuracy&quot;))
summ(Post_4_India)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: accuracy
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 5.20, p = 0.01
## R² = 0.01
## Adj. R² = 0.01 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  2.20   0.05    42.20   0.00
## conditioncorrection         -0.17   0.07    -2.36   0.02
## conditionlink               -0.23   0.07    -3.09   0.00
## --------------------------------------------------------</code></pre>
</div>
<div id="plots-10" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>Post_1_India_ &lt;- ggpredict(Post_1_India, terms = c(&quot;condition&quot;))
Post_2_India_ &lt;- ggpredict(Post_2_India, terms = c(&quot;condition&quot;))
Post_3_India_ &lt;- ggpredict(Post_3_India, terms = c(&quot;condition&quot;))
Post_4_India_ &lt;- ggpredict(Post_4_India, terms = c(&quot;condition&quot;))

Post_1_India_plot &lt;- ggplot(Post_1_India_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India_Post_1&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_2_India_plot &lt;- ggplot(Post_2_India_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India_Post_2&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_3_India_plot &lt;- ggplot(Post_3_India_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India_Post_3&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_4_India_plot &lt;- ggplot(Post_4_India_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India_Post_4&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_1_India_plot + Post_2_India_plot + Post_3_India_plot + Post_4_India_plot</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
</div>
</div>
<div id="individual-posts-uk---sharing" class="section level2">
<h2>Individual posts UK - Sharing</h2>
<div id="models-13" class="section level3">
<h3>Models</h3>
<pre class="r"><code>Post_1_UK &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;UK&quot;&amp; post==&quot;false_1_sharing&quot;))
summ(Post_1_UK)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.43, p = 0.65
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.50   0.05    10.84   0.00
## conditioncorrection         -0.01   0.07    -0.19   0.85
## conditionlink               -0.06   0.06    -0.88   0.38
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_2_UK &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;UK&quot;&amp; post==&quot;false_2_sharing&quot;))
summ(Post_2_UK)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.03, p = 0.97
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.40   0.04     9.38   0.00
## conditioncorrection         -0.00   0.06    -0.03   0.97
## conditionlink               -0.01   0.06    -0.24   0.81
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_3_UK &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;UK&quot;&amp; post==&quot;false_3_sharing&quot;))
summ(Post_3_UK)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.08, p = 0.92
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.48   0.05    10.62   0.00
## conditioncorrection         -0.03   0.07    -0.39   0.69
## conditionlink               -0.02   0.06    -0.29   0.77
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_4_UK &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;UK&quot;&amp; post==&quot;false_4_sharing&quot;))
summ(Post_4_UK)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 1.07, p = 0.34
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.48   0.04    11.23   0.00
## conditioncorrection          0.01   0.06     0.09   0.93
## conditionlink               -0.07   0.06    -1.22   0.22
## --------------------------------------------------------</code></pre>
</div>
<div id="plots-11" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>Post_1_UK_ &lt;- ggpredict(Post_1_UK, terms = c(&quot;condition&quot;))
Post_2_UK_ &lt;- ggpredict(Post_2_UK, terms = c(&quot;condition&quot;))
Post_3_UK_ &lt;- ggpredict(Post_3_UK, terms = c(&quot;condition&quot;))
Post_4_UK_ &lt;- ggpredict(Post_4_UK, terms = c(&quot;condition&quot;))

Post_1_UK_plot &lt;- ggplot(Post_1_UK_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK_Post_1&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_2_UK_plot &lt;- ggplot(Post_2_UK_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK_Post_2&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_3_UK_plot &lt;- ggplot(Post_3_UK_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK_Post_3&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_4_UK_plot &lt;- ggplot(Post_4_UK_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK_Post_4&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_1_UK_plot + Post_2_UK_plot + Post_3_UK_plot + Post_4_UK_plot</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
</div>
</div>
<div id="individual-posts-brazil---sharing" class="section level2">
<h2>Individual posts Brazil - Sharing</h2>
<div id="models-14" class="section level3">
<h3>Models</h3>
<pre class="r"><code>Post_1_Bra &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;Brazil&quot;&amp; post==&quot;false_1_sharing&quot;))
summ(Post_1_Bra)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 1.87, p = 0.16
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.95   0.06    15.94   0.00
## conditioncorrection         -0.16   0.08    -1.90   0.06
## conditionlink               -0.05   0.08    -0.65   0.52
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_2_Bra &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;Brazil&quot;&amp; post==&quot;false_2_sharing&quot;))
summ(Post_2_Bra)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.59, p = 0.55
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.56   0.05    11.26   0.00
## conditioncorrection         -0.03   0.07    -0.37   0.71
## conditionlink                0.05   0.07     0.69   0.49
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_3_Bra &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;Brazil&quot;&amp; post==&quot;false_3_sharing&quot;))
summ(Post_3_Bra)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 3.18, p = 0.04
## R² = 0.01
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.58   0.05    11.76   0.00
## conditioncorrection         -0.12   0.07    -1.70   0.09
## conditionlink               -0.17   0.07    -2.47   0.01
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_4_Bra &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;Brazil&quot;&amp; post==&quot;false_4_sharing&quot;))
summ(Post_4_Bra)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 2.25, p = 0.11
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  0.73   0.05    13.69   0.00
## conditioncorrection         -0.16   0.07    -2.09   0.04
## conditionlink               -0.10   0.07    -1.38   0.17
## --------------------------------------------------------</code></pre>
</div>
<div id="plots-12" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>Post_1_Bra_ &lt;- ggpredict(Post_1_Bra, terms = c(&quot;condition&quot;))
Post_2_Bra_ &lt;- ggpredict(Post_2_Bra, terms = c(&quot;condition&quot;))
Post_3_Bra_ &lt;- ggpredict(Post_3_Bra, terms = c(&quot;condition&quot;))
Post_4_Bra_ &lt;- ggpredict(Post_4_Bra, terms = c(&quot;condition&quot;))

Post_1_Bra_plot &lt;- ggplot(Post_1_Bra_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Bra_Post_1&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_2_Bra_plot &lt;- ggplot(Post_2_Bra_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Bra_Post_2&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_3_Bra_plot &lt;- ggplot(Post_3_Bra_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Bra_Post_3&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_4_Bra_plot &lt;- ggplot(Post_4_Bra_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Bra_Post_4&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_1_Bra_plot + Post_2_Bra_plot + Post_3_Bra_plot + Post_4_Bra_plot</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
</div>
</div>
<div id="individual-posts-india---sharing" class="section level2">
<h2>Individual posts India - Sharing</h2>
<div id="models-15" class="section level3">
<h3>Models</h3>
<pre class="r"><code>Post_1_India &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;India&quot;&amp; post==&quot;false_1_sharing&quot;))
summ(Post_1_India)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 0.55, p = 0.58
## R² = 0.00
## Adj. R² = -0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  1.42   0.06    21.98   0.00
## conditioncorrection         -0.03   0.09    -0.30   0.77
## conditionlink               -0.09   0.09    -1.02   0.31
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_2_India &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;India&quot;&amp; post==&quot;false_2_sharing&quot;))
summ(Post_2_India)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 2.51, p = 0.08
## R² = 0.01
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  1.66   0.06    27.23   0.00
## conditioncorrection         -0.04   0.09    -0.46   0.64
## conditionlink               -0.18   0.09    -2.13   0.03
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_3_India &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;India&quot;&amp; post==&quot;false_3_sharing&quot;))
summ(Post_3_India)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 1.33, p = 0.27
## R² = 0.00
## Adj. R² = 0.00 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  1.32   0.07    19.11   0.00
## conditioncorrection         -0.06   0.10    -0.63   0.53
## conditionlink               -0.16   0.10    -1.62   0.11
## --------------------------------------------------------</code></pre>
<pre class="r"><code>Post_4_India &lt;- lm(sharing ~ condition, data=subset(corrections_sharing_long, country==&quot;India&quot;&amp; post==&quot;false_4_sharing&quot;))
summ(Post_4_India)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 1000
## Dependent Variable: sharing
## Type: OLS linear regression 
## 
## MODEL FIT:
## F(2,997) = 4.70, p = 0.01
## R² = 0.01
## Adj. R² = 0.01 
## 
## Standard errors: OLS
## --------------------------------------------------------
##                              Est.   S.E.   t val.      p
## ------------------------- ------- ------ -------- ------
## (Intercept)                  2.03   0.06    34.67   0.00
## conditioncorrection         -0.17   0.08    -2.03   0.04
## conditionlink               -0.25   0.08    -3.01   0.00
## --------------------------------------------------------</code></pre>
</div>
<div id="plots-13" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>Post_1_India_ &lt;- ggpredict(Post_1_India, terms = c(&quot;condition&quot;))
Post_2_India_ &lt;- ggpredict(Post_2_India, terms = c(&quot;condition&quot;))
Post_3_India_ &lt;- ggpredict(Post_3_India, terms = c(&quot;condition&quot;))
Post_4_India_ &lt;- ggpredict(Post_4_India, terms = c(&quot;condition&quot;))

Post_1_India_plot &lt;- ggplot(Post_1_India_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India_Post_1&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_2_India_plot &lt;- ggplot(Post_2_India_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India_Post_2&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_3_India_plot &lt;- ggplot(Post_3_India_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India_Post_3&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_4_India_plot &lt;- ggplot(Post_4_India_, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India_Post_4&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

Post_1_India_plot + Post_2_India_plot + Post_3_India_plot + Post_4_India_plot</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
</div>
</div>
<div id="determinants-of-belief" class="section level2">
<h2>Determinants of belief</h2>
<pre class="r"><code>corrections_accuracy_long_ALL &lt;- melt(corrections_merged, id.vars = c(&quot;ResponseId&quot;, &quot;condition&quot;, &quot;country&quot;, &quot;consp_mean&quot;,&quot;Trust_SM&quot;,&quot;Trust_News&quot;,&quot;Trust_Scientist&quot;,&quot;Trust_Ordinary_ppl&quot;,&quot;age&quot;,&quot;gender&quot;,&quot;education&quot;), 
              measure.vars = c(&quot;false_1_accuracy&quot;, &quot;false_2_accuracy&quot;, &quot;false_3_accuracy&quot;, &quot;false_4_accuracy&quot;,&quot;uncorrected_1_accuracy&quot;, &quot;uncorrected_2_accuracy&quot;), 
              variable.name = &quot;post&quot;, 
              value.name=&quot;accuracy&quot;)

Explo_3 &lt;- lmer(accuracy ~ consp_mean  + Trust_SM + Trust_News +Trust_Scientist+Trust_Ordinary_ppl+age+gender +education+ condition + (1|post:country)+(1 | ResponseId), data=corrections_accuracy_long_ALL) 
summ(Explo_3)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 18000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 45928.58, BIC = 46037.75
## Pseudo-R² (fixed effects) = 0.15
## Pseudo-R² (total) = 0.47 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  1.16   0.09    13.58     38.81   0.00
## consp_mean                   0.17   0.01    13.43   2990.80   0.00
## Trust_SM                     0.15   0.01    11.47   2997.75   0.00
## Trust_News                   0.01   0.01     1.09   2989.06   0.28
## Trust_Scientist             -0.14   0.01   -10.82   2987.49   0.00
## Trust_Ordinary_ppl           0.13   0.01    10.46   2993.70   0.00
## age                         -0.03   0.01    -3.12   2996.90   0.00
## gender                       0.00   0.00     0.78   2986.82   0.44
## education                    0.00   0.00     0.60   2990.85   0.55
## conditioncorrection         -0.05   0.03    -1.72   2986.80   0.09
## conditionlink               -0.08   0.03    -2.92   2986.78   0.00
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.53    
##  post:country   (Intercept)     0.29    
##    Residual                     0.77    
## ----------------------------------------
## 
## Grouping variables:
## --------------------------------
##     Group       # groups   ICC  
## -------------- ---------- ------
##   ResponseId      3000     0.29 
##  post:country      18      0.09 
## --------------------------------</code></pre>
<pre class="r"><code>Explo_3_UK &lt;- lmer(accuracy ~ consp_mean  + Trust_SM + Trust_News +Trust_Scientist+Trust_Ordinary_ppl+age+gender +education+ condition +(1 | ResponseId)+ (1 | post), data=subset(corrections_accuracy_long_ALL, country==&quot;UK&quot;))
summ(Explo_3_UK) </code></pre>
<pre><code>## MODEL INFO:
## Observations: 6000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 12833.07, BIC = 12926.86
## Pseudo-R² (fixed effects) = 0.21
## Pseudo-R² (total) = 0.50 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------
##                              Est.   S.E.   t val.     d.f.      p
## ------------------------- ------- ------ -------- -------- ------
## (Intercept)                  0.91   0.12     7.53    16.52   0.00
## consp_mean                   0.18   0.02    10.66   989.00   0.00
## Trust_SM                     0.17   0.02     8.17   989.00   0.00
## Trust_News                   0.02   0.02     0.99   989.00   0.32
## Trust_Scientist             -0.12   0.02    -7.10   989.00   0.00
## Trust_Ordinary_ppl           0.11   0.02     5.56   989.00   0.00
## age                         -0.02   0.01    -1.80   989.00   0.07
## gender                      -0.00   0.00    -0.52   989.00   0.60
## education                   -0.00   0.01    -0.02   989.00   0.98
## conditioncorrection         -0.03   0.04    -0.70   989.00   0.48
## conditionlink               -0.03   0.04    -0.91   989.00   0.36
## -----------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.42    
##     post      (Intercept)     0.22    
##   Residual                    0.63    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.29 
##     post         6       0.08 
## ------------------------------</code></pre>
<pre class="r"><code>Explo_3_BRA &lt;- lmer(accuracy ~ consp_mean  + Trust_SM + Trust_News +Trust_Scientist+Trust_Ordinary_ppl+age+gender +education+ condition +(1 | ResponseId)+ (1 | post), data=subset(corrections_accuracy_long_ALL, country==&quot;Brazil&quot;))
summ(Explo_3_BRA) </code></pre>
<pre><code>## MODEL INFO:
## Observations: 6000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 16099.17, BIC = 16192.97
## Pseudo-R² (fixed effects) = 0.07
## Pseudo-R² (total) = 0.34 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------
##                              Est.   S.E.   t val.     d.f.      p
## ------------------------- ------- ------ -------- -------- ------
## (Intercept)                  1.50   0.15    10.02    18.26   0.00
## consp_mean                   0.11   0.02     4.58   989.00   0.00
## Trust_SM                     0.07   0.02     3.15   989.00   0.00
## Trust_News                  -0.11   0.02    -5.64   989.00   0.00
## Trust_Scientist             -0.11   0.02    -5.01   989.00   0.00
## Trust_Ordinary_ppl           0.11   0.02     5.25   989.00   0.00
## age                         -0.01   0.01    -0.73   989.00   0.46
## gender                       0.01   0.00     1.60   989.00   0.11
## education                   -0.02   0.01    -1.14   989.00   0.25
## conditioncorrection         -0.06   0.05    -1.25   989.00   0.21
## conditionlink               -0.07   0.05    -1.55   989.00   0.12
## -----------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.47    
##     post      (Intercept)     0.26    
##   Residual                    0.84    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.22 
##     post         6       0.07 
## ------------------------------</code></pre>
<pre class="r"><code>Explo_3_IND &lt;- lmer(accuracy ~ consp_mean  + Trust_SM + Trust_News +Trust_Scientist+Trust_Ordinary_ppl+age+gender +education+ condition +(1 | ResponseId)+ (1 | post), data=subset(corrections_accuracy_long_ALL, country==&quot;India&quot;))
summ(Explo_3_IND) </code></pre>
<pre><code>## MODEL INFO:
## Observations: 6000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 16351.58, BIC = 16445.38
## Pseudo-R² (fixed effects) = 0.16
## Pseudo-R² (total) = 0.50 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------
##                              Est.   S.E.   t val.     d.f.      p
## ------------------------- ------- ------ -------- -------- ------
## (Intercept)                  1.03   0.16     6.30    14.76   0.00
## consp_mean                   0.19   0.02     7.59   989.00   0.00
## Trust_SM                     0.16   0.02     6.67   989.00   0.00
## Trust_News                   0.15   0.03     5.83   989.00   0.00
## Trust_Scientist             -0.15   0.03    -5.63   989.00   0.00
## Trust_Ordinary_ppl           0.13   0.02     5.96   989.00   0.00
## age                         -0.05   0.02    -2.52   989.00   0.01
## gender                       0.01   0.01     1.37   989.00   0.17
## education                    0.00   0.00     0.70   989.00   0.49
## conditioncorrection         -0.06   0.06    -1.04   989.00   0.30
## conditionlink               -0.12   0.05    -2.24   989.00   0.03
## -----------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.62    
##     post      (Intercept)     0.30    
##   Residual                    0.83    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.33 
##     post         6       0.08 
## ------------------------------</code></pre>
</div>
<div id="determinants-of-sharing" class="section level2">
<h2>Determinants of sharing</h2>
<pre class="r"><code>corrections_sharing_long_ALL &lt;- melt(corrections_merged, id.vars = c(&quot;ResponseId&quot;, &quot;condition&quot;, &quot;country&quot;, &quot;consp_mean&quot;,&quot;Trust_SM&quot;,&quot;Trust_News&quot;,&quot;Trust_Scientist&quot;,&quot;Trust_Ordinary_ppl&quot;,&quot;age&quot;,&quot;gender&quot;,&quot;education&quot;), 
              measure.vars = c(&quot;false_1_sharing&quot;, &quot;false_2_sharing&quot;, &quot;false_3_sharing&quot;, &quot;false_4_sharing&quot;,&quot;uncorrected_1_sharing&quot;, &quot;uncorrected_2_sharing&quot;), 
              variable.name = &quot;post&quot;, 
              value.name=&quot;sharing&quot;)

Explo_4 &lt;- lmer(sharing ~ consp_mean  + Trust_SM + Trust_News +Trust_Scientist+Trust_Ordinary_ppl+age+gender +education + condition + (1|post:country)+(1 | ResponseId), data=corrections_sharing_long_ALL)
summ(Explo_4)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 18000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 41789.90, BIC = 41899.07
## Pseudo-R² (fixed effects) = 0.20
## Pseudo-R² (total) = 0.62 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  0.74   0.08     8.78     52.04   0.00
## consp_mean                   0.14   0.01     9.85   2991.98   0.00
## Trust_SM                     0.22   0.01    14.57   3000.99   0.00
## Trust_News                   0.04   0.01     2.67   2989.42   0.01
## Trust_Scientist             -0.12   0.01    -8.73   2987.01   0.00
## Trust_Ordinary_ppl           0.14   0.01    10.06   2996.10   0.00
## age                         -0.04   0.01    -3.73   3000.04   0.00
## gender                       0.00   0.00     0.62   2985.98   0.53
## education                    0.00   0.00     0.80   2992.05   0.42
## conditioncorrection         -0.05   0.03    -1.71   2985.93   0.09
## conditionlink               -0.07   0.03    -2.40   2985.91   0.02
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.64    
##  post:country   (Intercept)     0.26    
##    Residual                     0.66    
## ----------------------------------------
## 
## Grouping variables:
## --------------------------------
##     Group       # groups   ICC  
## -------------- ---------- ------
##   ResponseId      3000     0.45 
##  post:country      18      0.08 
## --------------------------------</code></pre>
<pre class="r"><code>Explo_4_UK &lt;- lmer(sharing ~ consp_mean  + Trust_SM + Trust_News +Trust_Scientist+Trust_Ordinary_ppl+age+gender +education+ condition +(1 | ResponseId)+ (1 | post), data=subset(corrections_sharing_long_ALL, country==&quot;UK&quot;))
summ(Explo_4_UK) </code></pre>
<pre><code>## MODEL INFO:
## Observations: 6000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 9473.23, BIC = 9567.03
## Pseudo-R² (fixed effects) = 0.32
## Pseudo-R² (total) = 0.70 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------
##                              Est.   S.E.   t val.     d.f.      p
## ------------------------- ------- ------ -------- -------- ------
## (Intercept)                  0.52   0.09     5.79   837.35   0.00
## consp_mean                   0.10   0.02     5.60   989.00   0.00
## Trust_SM                     0.24   0.02    10.90   989.00   0.00
## Trust_News                   0.04   0.02     1.85   989.00   0.07
## Trust_Scientist             -0.09   0.02    -4.94   989.00   0.00
## Trust_Ordinary_ppl           0.11   0.02     5.18   989.00   0.00
## age                         -0.07   0.01    -5.29   989.00   0.00
## gender                      -0.00   0.00    -0.33   989.00   0.74
## education                    0.01   0.01     0.54   989.00   0.59
## conditioncorrection         -0.01   0.04    -0.20   989.00   0.84
## conditionlink               -0.02   0.04    -0.42   989.00   0.67
## -----------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.50    
##     post      (Intercept)     0.04    
##   Residual                    0.44    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.57 
##     post         6       0.00 
## ------------------------------</code></pre>
<pre class="r"><code>Explo_4_BRA &lt;- lmer(sharing ~ consp_mean  + Trust_SM + Trust_News +Trust_Scientist+Trust_Ordinary_ppl+age+gender +education+ condition +(1 | ResponseId)+ (1 | post), data=subset(corrections_sharing_long_ALL, country==&quot;Brazil&quot;))
summ(Explo_4_BRA) </code></pre>
<pre><code>## MODEL INFO:
## Observations: 6000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 14780.72, BIC = 14874.51
## Pseudo-R² (fixed effects) = 0.08
## Pseudo-R² (total) = 0.50 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------
##                              Est.   S.E.   t val.     d.f.      p
## ------------------------- ------- ------ -------- -------- ------
## (Intercept)                  1.12   0.14     7.90    82.31   0.00
## consp_mean                   0.09   0.03     3.19   989.01   0.00
## Trust_SM                     0.14   0.03     5.14   989.01   0.00
## Trust_News                  -0.08   0.02    -3.47   989.01   0.00
## Trust_Scientist             -0.11   0.03    -4.27   989.01   0.00
## Trust_Ordinary_ppl           0.13   0.03     5.18   989.01   0.00
## age                          0.01   0.02     0.58   989.01   0.56
## gender                       0.00   0.01     0.63   989.01   0.53
## education                   -0.04   0.02    -2.68   989.01   0.01
## conditioncorrection         -0.10   0.05    -1.86   989.01   0.06
## conditionlink               -0.06   0.05    -1.12   989.01   0.27
## -----------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.63    
##     post      (Intercept)     0.17    
##   Residual                    0.71    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.43 
##     post         6       0.03 
## ------------------------------</code></pre>
<pre class="r"><code>Explo_4_IND &lt;- lmer(sharing ~ consp_mean  + Trust_SM + Trust_News +Trust_Scientist+Trust_Ordinary_ppl+age+gender +education+ condition +(1 | ResponseId)+ (1 | post), data=subset(corrections_sharing_long_ALL, country==&quot;India&quot;))
summ(Explo_4_IND) </code></pre>
<pre><code>## MODEL INFO:
## Observations: 6000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 15798.45, BIC = 15892.25
## Pseudo-R² (fixed effects) = 0.20
## Pseudo-R² (total) = 0.58 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------
##                              Est.   S.E.   t val.     d.f.      p
## ------------------------- ------- ------ -------- -------- ------
## (Intercept)                  0.71   0.15     4.71    30.66   0.00
## consp_mean                   0.20   0.03     7.22   989.00   0.00
## Trust_SM                     0.20   0.03     7.48   989.00   0.00
## Trust_News                   0.18   0.03     6.32   989.00   0.00
## Trust_Scientist             -0.14   0.03    -4.71   989.00   0.00
## Trust_Ordinary_ppl           0.14   0.02     5.79   989.00   0.00
## age                         -0.04   0.02    -1.76   989.00   0.08
## gender                       0.02   0.01     1.96   989.00   0.05
## education                    0.00   0.00     0.92   989.00   0.36
## conditioncorrection         -0.05   0.06    -0.80   989.00   0.43
## conditionlink               -0.13   0.06    -2.22   989.00   0.03
## -----------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.70    
##     post      (Intercept)     0.23    
##   Residual                    0.77    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.43 
##     post         6       0.05 
## ------------------------------</code></pre>
</div>
<div id="spillover-effect-on-uncorrected-false-posts---accuracy" class="section level2">
<h2>Spillover effect on uncorrected FALSE posts - Accuracy</h2>
<div id="models-16" class="section level3">
<h3>Models</h3>
<pre class="r"><code>corrections_accuracy_long_uncorrected &lt;- melt(corrections_merged, id.vars = c(&quot;ResponseId&quot;, &quot;condition&quot;, &quot;country&quot;, &quot;consp_mean&quot;,&quot;Trust_SM&quot;,&quot;Trust_News&quot;,&quot;Trust_Scientist&quot;,&quot;Trust_Ordinary_ppl&quot;,&quot;age&quot;,&quot;gender&quot;,&quot;education&quot;), 
              measure.vars = c(&quot;uncorrected_1_accuracy&quot;, &quot;uncorrected_2_accuracy&quot;), 
              variable.name = &quot;post&quot;, 
              value.name=&quot;accuracy&quot;)

h1a_all &lt;- lmer(accuracy ~ condition +(1|post:country)+ (1 | ResponseId), data=corrections_accuracy_long_uncorrected)
summ(h1a_all)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 6000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 16714.35, BIC = 16754.54
## Pseudo-R² (fixed effects) = 0.00
## Pseudo-R² (total) = 0.50 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  1.07   0.15     6.95      5.23   0.00
## conditioncorrection          0.04   0.04     1.05   2994.96   0.29
## conditionlink               -0.06   0.04    -1.48   2994.95   0.14
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.68    
##  post:country   (Intercept)     0.37    
##    Residual                     0.77    
## ----------------------------------------
## 
## Grouping variables:
## --------------------------------
##     Group       # groups   ICC  
## -------------- ---------- ------
##   ResponseId      3000     0.39 
##  post:country      6       0.12 
## --------------------------------</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_all)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink 
##             0.00000           -96.18397          -105.32047</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_all)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink 
##           35.820585            1.366925           -1.905824</code></pre>
<pre class="r"><code>h1a_uk &lt;- lmer(accuracy ~ condition + post + (1 | ResponseId), data=subset(corrections_accuracy_long_uncorrected, country==&quot;UK&quot;))
summ(h1a_uk)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 2000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 4662.94, BIC = 4696.54
## Pseudo-R² (fixed effects) = 0.05
## Pseudo-R² (total) = 0.53 
## 
## FIXED EFFECTS:
## -------------------------------------------------------------------------
##                                     Est.   S.E.   t val.      d.f.      p
## -------------------------------- ------- ------ -------- --------- ------
## (Intercept)                         0.85   0.04    20.50   1215.73   0.00
## conditioncorrection                 0.01   0.06     0.12    997.00   0.91
## conditionlink                      -0.04   0.06    -0.71    997.00   0.48
## postuncorrected_2_accuracy         -0.36   0.03   -13.97    999.00   0.00
## -------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.59    
##   Residual                    0.58    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.50 
## ------------------------------</code></pre>
<pre class="r"><code>h1a_brazil &lt;- lmer(accuracy ~ condition +  post+(1 | ResponseId), data=subset(corrections_accuracy_long_uncorrected, country==&quot;Brazil&quot;))
summ(h1a_brazil)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 2000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 5705.50, BIC = 5739.11
## Pseudo-R² (fixed effects) = 0.00
## Pseudo-R² (total) = 0.32 
## 
## FIXED EFFECTS:
## -------------------------------------------------------------------------
##                                     Est.   S.E.   t val.      d.f.      p
## -------------------------------- ------- ------ -------- --------- ------
## (Intercept)                         1.13   0.05    22.52   1324.41   0.00
## conditioncorrection                 0.03   0.06     0.44    997.00   0.66
## conditionlink                      -0.10   0.06    -1.50    997.00   0.13
## postuncorrected_2_accuracy          0.05   0.04     1.24    999.00   0.22
## -------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.58    
##   Residual                    0.85    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.32 
## ------------------------------</code></pre>
<pre class="r"><code>h1a_india &lt;- lmer(accuracy ~ condition + post + (1 | ResponseId), data=subset(corrections_accuracy_long_uncorrected, country==&quot;India&quot;))
summ(h1a_india)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 2000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 6086.14, BIC = 6119.74
## Pseudo-R² (fixed effects) = 0.01
## Pseudo-R² (total) = 0.50 
## 
## FIXED EFFECTS:
## -------------------------------------------------------------------------
##                                     Est.   S.E.   t val.      d.f.      p
## -------------------------------- ------- ------ -------- --------- ------
## (Intercept)                         1.29   0.06    21.77   1215.51   0.00
## conditioncorrection                 0.09   0.08     1.09    997.00   0.28
## conditionlink                      -0.04   0.08    -0.45    997.00   0.65
## postuncorrected_2_accuracy          0.24   0.04     6.32    999.00   0.00
## -------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.83    
##   Residual                    0.84    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.50 
## ------------------------------</code></pre>
</div>
<div id="plots-14" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>h1a_uk_results &lt;- ggpredict(h1a_uk, terms = c(&quot;condition&quot;))
h1a_brazil_results &lt;- ggpredict(h1a_brazil, terms = c(&quot;condition&quot;))
h1a_india_results &lt;- ggpredict(h1a_india, terms = c(&quot;condition&quot;))</code></pre>
<pre class="r"><code>h1a_uk_plot &lt;- ggplot(h1a_uk_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK - uncorrected posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

h1a_brazil_plot &lt;- ggplot(h1a_brazil_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
  scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
  ylab(&quot;Accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Brazil - uncorrected posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        legend.position = &quot;none&quot;)

h1a_india_plot &lt;- ggplot(h1a_india_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
  scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
  ylab(&quot;Accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India - uncorrected posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)</code></pre>
</div>
</div>
<div id="spillover-effect-on-true-posts---accuracy" class="section level2">
<h2>Spillover effect on TRUE posts - Accuracy</h2>
<div id="models-17" class="section level3">
<h3>Models</h3>
<pre class="r"><code>corrections_accuracy_long_real &lt;- melt(corrections_merged, id.vars = c(&quot;ResponseId&quot;, &quot;condition&quot;, &quot;country&quot;, &quot;consp_mean&quot;,&quot;Trust_SM&quot;,&quot;Trust_News&quot;,&quot;Trust_Scientist&quot;,&quot;Trust_Ordinary_ppl&quot;,&quot;age&quot;,&quot;gender&quot;,&quot;education&quot;), 
               measure.vars = c(&quot;real_1_accuracy&quot;, &quot;real_2_accuracy&quot;,&quot;real_3_accuracy&quot;), 
               variable.name = &quot;post&quot;, 
               value.name=&quot;accuracy&quot;)

h1a_all &lt;- lmer(accuracy ~ condition + (1|post:country) + (1 | ResponseId), data=corrections_accuracy_long_real)
summ(h1a_all)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 9000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 22290.29, BIC = 22332.92
## Pseudo-R² (fixed effects) = 0.00
## Pseudo-R² (total) = 0.37 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------
##                             Est.   S.E.   t val.      d.f.      p
## ------------------------- ------ ------ -------- --------- ------
## (Intercept)                 2.06   0.09    23.81      8.79   0.00
## conditioncorrection         0.00   0.03     0.08   2995.05   0.94
## conditionlink               0.04   0.03     1.40   2995.03   0.16
## -----------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.49    
##  post:country   (Intercept)     0.25    
##    Residual                     0.72    
## ----------------------------------------
## 
## Grouping variables:
## --------------------------------
##     Group       # groups   ICC  
## -------------- ---------- ------
##   ResponseId      3000     0.29 
##  post:country      9       0.08 
## --------------------------------</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_all)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink 
##             0.00000           -99.88987           -98.05891</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_all)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink 
##         68.57651267          0.07552178          1.33113296</code></pre>
<pre class="r"><code>h1a_uk &lt;- lmer(accuracy ~ condition + post + (1 | ResponseId), data=subset(corrections_accuracy_long_real, country==&quot;UK&quot;))
summ(h1a_uk)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 3000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 6677.31, BIC = 6719.36
## Pseudo-R² (fixed effects) = 0.01
## Pseudo-R² (total) = 0.43 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  2.03   0.04    54.53   1435.52   0.00
## conditioncorrection         -0.02   0.05    -0.45    997.00   0.65
## conditionlink                0.08   0.05     1.74    997.00   0.08
## postreal_2_accuracy          0.16   0.03     6.03   1998.00   0.00
## postreal_3_accuracy          0.19   0.03     6.92   1998.00   0.00
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.51    
##   Residual                    0.60    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.42 
## ------------------------------</code></pre>
<pre class="r"><code>h1a_brazil &lt;- lmer(accuracy ~ condition +  post+(1 | ResponseId), data=subset(corrections_accuracy_long_real, country==&quot;Brazil&quot;))
summ(h1a_brazil)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 3000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 8063.18, BIC = 8105.22
## Pseudo-R² (fixed effects) = 0.14
## Pseudo-R² (total) = 0.27 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  2.45   0.04    60.03   1844.01   0.00
## conditioncorrection          0.03   0.05     0.52    997.00   0.60
## conditionlink                0.07   0.05     1.43    997.00   0.15
## postreal_2_accuracy         -0.86   0.04   -22.53   1998.00   0.00
## postreal_3_accuracy         -0.70   0.04   -18.27   1998.00   0.00
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.37    
##   Residual                    0.86    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.16 
## ------------------------------</code></pre>
<pre class="r"><code>h1a_india &lt;- lmer(accuracy ~ condition + post + (1 | ResponseId), data=subset(corrections_accuracy_long_real, country==&quot;India&quot;))
summ(h1a_india)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 3000
## Dependent Variable: accuracy
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 7314.35, BIC = 7356.39
## Pseudo-R² (fixed effects) = 0.00
## Pseudo-R² (total) = 0.41 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  2.08   0.04    50.24   1442.91   0.00
## conditioncorrection          0.00   0.05     0.05    997.00   0.96
## conditionlink               -0.03   0.05    -0.61    997.00   0.54
## postreal_2_accuracy          0.01   0.03     0.30   1998.00   0.77
## postreal_3_accuracy          0.06   0.03     2.08   1998.00   0.04
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.56    
##   Residual                    0.68    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.40 
## ------------------------------</code></pre>
</div>
<div id="plots-15" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>h1a_uk_results &lt;- ggpredict(h1a_uk, terms = c(&quot;condition&quot;))
h1a_brazil_results &lt;- ggpredict(h1a_brazil, terms = c(&quot;condition&quot;))
h1a_india_results &lt;- ggpredict(h1a_india, terms = c(&quot;condition&quot;))</code></pre>
<pre class="r"><code>h1a_uk_plot &lt;- ggplot(h1a_uk_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n accurate&quot;, &quot;Not very\n accurate&quot;, &quot;Somewhat\n accurate&quot;, &quot;Very\n accurate&quot;)) +
  ylab(&quot;Percieved accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK - true posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

h1a_brazil_plot &lt;- ggplot(h1a_brazil_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
  scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
  ylab(&quot;Accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Brazil - true posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        legend.position = &quot;none&quot;)

h1a_india_plot &lt;- ggplot(h1a_india_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
  scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
  ylab(&quot;Accuracy&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India - true posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)</code></pre>
</div>
</div>
<div id="spillover-effect-on-uncorrected-false-posts---sharing" class="section level2">
<h2>Spillover effect on uncorrected FALSE posts - Sharing</h2>
<div id="models-18" class="section level3">
<h3>Models</h3>
<pre class="r"><code>corrections_sharing_long_uncorrected &lt;- melt(corrections_merged, id.vars = c(&quot;ResponseId&quot;, &quot;condition&quot;, &quot;country&quot;, &quot;consp_mean&quot;,&quot;Trust_SM&quot;,&quot;Trust_News&quot;,&quot;Trust_Scientist&quot;,&quot;Trust_Ordinary_ppl&quot;,&quot;age&quot;,&quot;gender&quot;,&quot;education&quot;), 
              measure.vars = c(&quot;uncorrected_1_sharing&quot;, &quot;uncorrected_2_sharing&quot;), 
              variable.name = &quot;post&quot;, 
              value.name=&quot;sharing&quot;)

h1a_all &lt;- lmer(sharing ~ condition + (1|post:country)+ (1 | ResponseId), data=corrections_sharing_long_uncorrected)
summ(h1a_all)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 6000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 16248.59, BIC = 16288.79
## Pseudo-R² (fixed effects) = 0.00
## Pseudo-R² (total) = 0.64 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  0.88   0.18     4.80      5.18   0.00
## conditioncorrection          0.06   0.04     1.34   2994.91   0.18
## conditionlink               -0.06   0.04    -1.52   2994.90   0.13
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.78    
##  post:country   (Intercept)     0.45    
##    Residual                     0.67    
## ----------------------------------------
## 
## Grouping variables:
## --------------------------------
##     Group       # groups   ICC  
## -------------- ---------- ------
##   ResponseId      3000     0.49 
##  post:country      6       0.16 
## --------------------------------</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_all)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink 
##             0.00000           -93.77102          -107.02675</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_all)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink 
##           29.454680            1.834725           -2.069707</code></pre>
<pre class="r"><code>h1a_uk &lt;- lmer(sharing ~ condition + post + (1 | ResponseId), data=subset(corrections_sharing_long_uncorrected, country==&quot;UK&quot;))
summ(h1a_uk)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 2000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 4223.60, BIC = 4257.20
## Pseudo-R² (fixed effects) = 0.00
## Pseudo-R² (total) = 0.67 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                    Est.   S.E.   t val.      d.f.      p
## ------------------------------- ------- ------ -------- --------- ------
## (Intercept)                        0.46   0.04    11.28   1130.72   0.00
## conditioncorrection                0.04   0.06     0.73    997.00   0.47
## conditionlink                     -0.06   0.06    -1.00    997.00   0.32
## postuncorrected_2_sharing         -0.08   0.02    -3.68    999.00   0.00
## ------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.65    
##   Residual                    0.46    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.67 
## ------------------------------</code></pre>
<pre class="r"><code>h1a_brazil &lt;- lmer(sharing ~ condition +  post+(1 | ResponseId), data=subset(corrections_sharing_long_uncorrected, country==&quot;Brazil&quot;))
summ(h1a_brazil)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 2000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 5606.31, BIC = 5639.91
## Pseudo-R² (fixed effects) = 0.01
## Pseudo-R² (total) = 0.52 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                    Est.   S.E.   t val.      d.f.      p
## ------------------------------- ------- ------ -------- --------- ------
## (Intercept)                        0.77   0.05    14.40   1204.46   0.00
## conditioncorrection               -0.02   0.07    -0.25    997.00   0.80
## conditionlink                     -0.09   0.07    -1.26    997.00   0.21
## postuncorrected_2_sharing          0.18   0.03     5.41    999.00   0.00
## ------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.75    
##   Residual                    0.74    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.51 
## ------------------------------</code></pre>
<pre class="r"><code>h1a_india &lt;- lmer(sharing ~ condition + post + (1 | ResponseId), data=subset(corrections_sharing_long_uncorrected, country==&quot;India&quot;))
summ(h1a_india)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 2000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 6018.10, BIC = 6051.71
## Pseudo-R² (fixed effects) = 0.01
## Pseudo-R² (total) = 0.59 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------------
##                                    Est.   S.E.   t val.      d.f.      p
## ------------------------------- ------- ------ -------- --------- ------
## (Intercept)                        1.29   0.06    20.99   1168.37   0.00
## conditioncorrection                0.14   0.08     1.70    997.00   0.09
## conditionlink                     -0.04   0.08    -0.50    997.00   0.62
## postuncorrected_2_sharing          0.16   0.03     4.59    999.00   0.00
## ------------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.92    
##   Residual                    0.77    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.58 
## ------------------------------</code></pre>
</div>
<div id="plots-16" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>h1a_uk_results &lt;- ggpredict(h1a_uk, terms = c(&quot;condition&quot;))
h1a_brazil_results &lt;- ggpredict(h1a_brazil, terms = c(&quot;condition&quot;))
h1a_india_results &lt;- ggpredict(h1a_india, terms = c(&quot;condition&quot;))</code></pre>
<pre class="r"><code>h1a_uk_plot &lt;- ggplot(h1a_uk_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n likely&quot;, &quot;Not very\n likely&quot;, &quot;Somewhat\n likely&quot;, &quot;Very\n likely&quot;)) +
  ylab(&quot;Likelihood of sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK - uncorrected false posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

h1a_brazil_plot &lt;- ggplot(h1a_brazil_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
  scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
  ylab(&quot;Likelihood of sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Brazil - uncorrected false posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        legend.position = &quot;none&quot;)

h1a_india_plot &lt;- ggplot(h1a_india_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
  scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
  ylab(&quot;Likelihood of sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India - uncorrected false posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)</code></pre>
</div>
</div>
<div id="spillover-effect-on-true-post---sharing" class="section level2">
<h2>Spillover effect on TRUE post - Sharing</h2>
<div id="models-19" class="section level3">
<h3>Models</h3>
<pre class="r"><code>corrections_sharing_long_uncorrected &lt;- melt(corrections_merged, id.vars = c(&quot;ResponseId&quot;, &quot;condition&quot;, &quot;country&quot;, &quot;consp_mean&quot;,&quot;Trust_SM&quot;,&quot;Trust_News&quot;,&quot;Trust_Scientist&quot;,&quot;Trust_Ordinary_ppl&quot;,&quot;age&quot;,&quot;gender&quot;,&quot;education&quot;), 
              measure.vars = c(&quot;real_1_sharing&quot;, &quot;real_2_sharing&quot;,&quot;real_3_sharing&quot;), 
              variable.name = &quot;post&quot;, 
              value.name=&quot;sharing&quot;)

h1a_all &lt;- lmer(sharing ~ condition + (1|post:country) + (1 | ResponseId), data=corrections_sharing_long_uncorrected)
summ(h1a_all)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 9000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 23815.89, BIC = 23858.52
## Pseudo-R² (fixed effects) = 0.00
## Pseudo-R² (total) = 0.64 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  1.40   0.17     8.24      8.32   0.00
## conditioncorrection         -0.01   0.04    -0.26   2994.92   0.79
## conditionlink               -0.02   0.04    -0.42   2994.91   0.67
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## ----------------------------------------
##     Group        Parameter    Std. Dev. 
## -------------- ------------- -----------
##   ResponseId    (Intercept)     0.78    
##  post:country   (Intercept)     0.50    
##    Residual                     0.70    
## ----------------------------------------
## 
## Grouping variables:
## --------------------------------
##     Group       # groups   ICC  
## -------------- ---------- ------
##   ResponseId      3000     0.45 
##  post:country      9       0.19 
## --------------------------------</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_all)
percent_increase &lt;- (coefs / coefs[1] - 1) * 100
percent_increase</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink 
##              0.0000           -100.7448           -101.1891</code></pre>
<pre class="r"><code>coefs &lt;- fixef(h1a_all)
pp_effects &lt;- (coefs / 3) * 100
pp_effects</code></pre>
<pre><code>##         (Intercept) conditioncorrection       conditionlink 
##          46.5873617          -0.3470055          -0.5539903</code></pre>
<pre class="r"><code>h1a_uk &lt;- lmer(sharing ~ condition + post + (1 | ResponseId), data=subset(corrections_sharing_long_uncorrected, country==&quot;UK&quot;))
summ(h1a_uk)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 3000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 6793.64, BIC = 6835.68
## Pseudo-R² (fixed effects) = 0.01
## Pseudo-R² (total) = 0.74 
## 
## FIXED EFFECTS:
## -----------------------------------------------------------------
##                             Est.   S.E.   t val.      d.f.      p
## ------------------------- ------ ------ -------- --------- ------
## (Intercept)                 0.74   0.05    14.46   1142.11   0.00
## conditioncorrection         0.05   0.07     0.75    997.00   0.45
## conditionlink               0.04   0.07     0.56    997.00   0.58
## postreal_2_sharing          0.02   0.02     0.78   1998.00   0.43
## postreal_3_sharing          0.20   0.02     8.79   1998.00   0.00
## -----------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.86    
##   Residual                    0.51    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.74 
## ------------------------------</code></pre>
<pre class="r"><code>h1a_brazil &lt;- lmer(sharing ~ condition +  post+(1 | ResponseId), data=subset(corrections_sharing_long_uncorrected, country==&quot;Brazil&quot;))
summ(h1a_brazil)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 3000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 8794.36, BIC = 8836.40
## Pseudo-R² (fixed effects) = 0.07
## Pseudo-R² (total) = 0.47 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  1.87   0.05    34.64   1409.26   0.00
## conditioncorrection         -0.07   0.07    -0.96    997.00   0.34
## conditionlink               -0.01   0.07    -0.18    997.00   0.86
## postreal_2_sharing          -0.72   0.04   -18.85   1998.00   0.00
## postreal_3_sharing          -0.60   0.04   -15.69   1998.00   0.00
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.74    
##   Residual                    0.86    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.43 
## ------------------------------</code></pre>
<pre class="r"><code>h1a_india &lt;- lmer(sharing ~ condition + post + (1 | ResponseId), data=subset(corrections_sharing_long_uncorrected, country==&quot;India&quot;))
summ(h1a_india)</code></pre>
<pre><code>## MODEL INFO:
## Observations: 3000
## Dependent Variable: sharing
## Type: Mixed effects linear regression 
## 
## MODEL FIT:
## AIC = 7741.38, BIC = 7783.43
## Pseudo-R² (fixed effects) = 0.00
## Pseudo-R² (total) = 0.54 
## 
## FIXED EFFECTS:
## ------------------------------------------------------------------
##                              Est.   S.E.   t val.      d.f.      p
## ------------------------- ------- ------ -------- --------- ------
## (Intercept)                  1.91   0.05    38.68   1294.30   0.00
## conditioncorrection         -0.02   0.06    -0.28    997.00   0.78
## conditionlink               -0.08   0.06    -1.20    997.00   0.23
## postreal_2_sharing           0.07   0.03     2.20   1998.00   0.03
## postreal_3_sharing           0.06   0.03     1.88   1998.00   0.06
## ------------------------------------------------------------------
## 
## p values calculated using Satterthwaite d.f.
## 
## RANDOM EFFECTS:
## --------------------------------------
##    Group       Parameter    Std. Dev. 
## ------------ ------------- -----------
##  ResponseId   (Intercept)     0.74    
##   Residual                    0.68    
## --------------------------------------
## 
## Grouping variables:
## ------------------------------
##    Group      # groups   ICC  
## ------------ ---------- ------
##  ResponseId     1000     0.54 
## ------------------------------</code></pre>
</div>
<div id="plots-17" class="section level3">
<h3>Plots</h3>
<pre class="r"><code>h1a_uk_results &lt;- ggpredict(h1a_uk, terms = c(&quot;condition&quot;))
h1a_brazil_results &lt;- ggpredict(h1a_brazil, terms = c(&quot;condition&quot;))
h1a_india_results &lt;- ggpredict(h1a_india, terms = c(&quot;condition&quot;))</code></pre>
<pre class="r"><code>h1a_uk_plot &lt;- ggplot(h1a_uk_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
    scale_y_continuous(limits = c(0,3), expand = c(0,0), labels=c(&quot;Not at all\n likely&quot;, &quot;Not very\n likely&quot;, &quot;Somewhat\n likely&quot;, &quot;Very\n likely&quot;)) +
  ylab(&quot;Likelihood of sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;UK - true posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)

h1a_brazil_plot &lt;- ggplot(h1a_brazil_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
  scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
  ylab(&quot;Likelihood of sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;Brazil - true posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        legend.position = &quot;none&quot;)

h1a_india_plot &lt;- ggplot(h1a_india_results, aes(x, predicted, fill=x)) +
  geom_bar(stat=&quot;identity&quot;) +
  geom_errorbar(aes(ymin=conf.low, ymax=conf.high), width=.2, position=position_dodge(.9)) +
  scale_x_discrete(labels=c(&quot;Control&quot;,&quot;Correction\n no link&quot;,&quot;Correction\n inc. link&quot;)) +
  scale_y_continuous(limits = c(0,3), expand = c(0,0)) +
  ylab(&quot;Likelihood of sharing&quot;) +
  xlab(&quot;Condition&quot;) +
  ggtitle(&quot;India - true posts&quot;) +
  scale_fill_manual(values=c(&quot;#b6bdc9&quot;, &quot;#01b2be&quot;, &quot;#82135f&quot;)) +
  theme_classic() +
  theme(axis.title.y=element_blank(),
        axis.text.y=element_blank(),
        axis.title.x=element_blank(),
        legend.position = &quot;none&quot;)</code></pre>
</div>
</div>



</div>
</div>

</div>

<script>

// add bootstrap table styles to pandoc tables
function bootstrapStylePandocTables() {
  $('tr.odd').parent('tbody').parent('table').addClass('table table-condensed');
}
$(document).ready(function () {
  bootstrapStylePandocTables();
});


</script>

<!-- tabsets -->

<script>
$(document).ready(function () {
  window.buildTabsets("TOC");
});

$(document).ready(function () {
  $('.tabset-dropdown > .nav-tabs > li').click(function () {
    $(this).parent().toggleClass('nav-tabs-open');
  });
});
</script>

<!-- code folding -->

<script>
$(document).ready(function ()  {

    // temporarily add toc-ignore selector to headers for the consistency with Pandoc
    $('.unlisted.unnumbered').addClass('toc-ignore')

    // move toc-ignore selectors from section div to header
    $('div.section.toc-ignore')
        .removeClass('toc-ignore')
        .children('h1,h2,h3,h4,h5').addClass('toc-ignore');

    // establish options
    var options = {
      selectors: "h1,h2,h3",
      theme: "bootstrap3",
      context: '.toc-content',
      hashGenerator: function (text) {
        return text.replace(/[.\\/?&!#<>]/g, '').replace(/\s/g, '_');
      },
      ignoreSelector: ".toc-ignore",
      scrollTo: 0
    };
    options.showAndHide = true;
    options.smoothScroll = true;

    // tocify
    var toc = $("#TOC").tocify(options).data("toc-tocify");
});
</script>

<!-- dynamically load mathjax for compatibility with self-contained -->
<script>
  (function () {
    var script = document.createElement("script");
    script.type = "text/javascript";
    script.src  = "https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML";
    document.getElementsByTagName("head")[0].appendChild(script);
  })();
</script>

</body>
</html>
